Results for 'classification'

697 found
Order:
  1. Potato Classification Using Deep Learning.Abeer A. Elsharif, Ibtesam M. Dheir, Alaa Soliman Abu Mettleq & Samy S. Abu-Naser - 2020 - International Journal of Academic Pedagogical Research (IJAPR) 3 (12):1-8.
    Abstract: Potatoes are edible tubers, available worldwide and all year long. They are relatively cheap to grow, rich in nutrients, and they can make a delicious treat. The humble potato has fallen in popularity in recent years, due to the interest in low-carb foods. However, the fiber, vitamins, minerals, and phytochemicals it provides can help ward off disease and benefit human health. They are an important staple food in many countries around the world. There are an estimated 200 varieties of (...)
    Download  
     
    Export citation  
     
    Bookmark   64 citations  
  2. Classification of Alzheimer's Disease Using Convolutional Neural Networks.Lamis F. Samhan, Amjad H. Alfarra & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (3):18-23.
    Brain-related diseases are among the most difficult diseases due to their sensitivity, the difficulty of performing operations, and their high costs. In contrast, the operation is not necessary to succeed, as the results of the operation may be unsuccessful. One of the most common diseases that affect the brain is Alzheimer’s disease, which affects adults, a disease that leads to memory loss and forgetting information in varying degrees. According to the condition of each patient. For these reasons, it is important (...)
    Download  
     
    Export citation  
     
    Bookmark   26 citations  
  3. Lemon Classification Using Deep Learning.Jawad Yousif AlZamily & Samy Salim Abu Naser - 2020 - International Journal of Academic Pedagogical Research (IJAPR) 3 (12):16-20.
    Abstract : Background: Vegetable agriculture is very important to human continued existence and remains a key driver of many economies worldwide, especially in underdeveloped and developing economies. Objectives: There is an increasing demand for food and cash crops, due to the increasing in world population and the challenges enforced by climate modifications, there is an urgent need to increase plant production while reducing costs. Methods: In this paper, Lemon classification approach is presented with a dataset that contains approximately 2,000 (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  4. Classification of Anomalies in Gastrointestinal Tract Using Deep Learning.Ibtesam M. Dheir & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):15-28.
    Automatic detection of diseases and anatomical landmarks in medical images by the use of computers is important and considered a challenging process that could help medical diagnosis and reduce the cost and time of investigational procedures and refine health care systems all over the world. Recently, gastrointestinal (GI) tract disease diagnosis through endoscopic image classification is an active research area in the biomedical field. Several GI tract disease classification methods based on image processing and machine learning techniques have (...)
    Download  
     
    Export citation  
     
    Bookmark   26 citations  
  5. Cantaloupe Classifications using Deep Learning.Basel El-Habil & Samy S. Abu-Naser - 2021 - International Journal of Academic Engineering Research (IJAER) 5 (12):7-17.
    Abstract cantaloupe and honeydew melons are part of the muskmelon family, which originated in the Middle East. When picking either cantaloupe or honeydew melons to eat, you should choose a firm fruit that is heavy for its size, with no obvious signs of bruising. They can be stored at room temperature until you cut them, after which they should be kept in the refrigerator in an airtight container for up to five days. You should always wash and scrub the rind (...)
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  6. Classification of A few Fruits Using Deep Learning.Mohammed Alkahlout, Samy S. Abu-Naser, Azmi H. Alsaqqa & Tanseem N. Abu-Jamie - 2022 - International Journal of Academic Engineering Research (IJAER) 5 (12):56-63.
    Abstract: Fruits are a rich source of energy, minerals and vitamins. They also contain fiber. There are many fruits types such as: Apple and pears, Citrus, Stone fruit, Tropical and exotic, Berries, Melons, Tomatoes and avocado. Classification of fruits can be used in many applications, whether industrial or in agriculture or services, for example, it can help the cashier in the hyper mall to determine the price and type of fruit and also may help some people to determining whether (...)
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  7. Rice Classification using ANN.Abdulrahman Muin Saad & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (10):32-42.
    Abstract: Rice, as a paramount staple crop worldwide, sustains billions of lives. Precise classification of rice types holds immense agricultural, nutritional, and economic significance. Recent advancements in machine learning, particularly Artificial Neural Networks (ANNs), offer promise in enhancing rice type classification accuracy and efficiency. This research explores rice type classification, harnessing neural networks' power. Utilizing a rich dataset from Kaggle, containing 18,188 entries and key rice grain attributes, we develop and evaluate a neural network model. Our neural (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  8. Glass Classification Using Artificial Neural Network.Mohmmad Jamal El-Khatib, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Pedagogical Research (IJAPR) 3 (23):25-31.
    As a type of evidence glass can be very useful contact trace material in a wide range of offences including burglaries and robberies, hit-and-run accidents, murders, assaults, ram-raids, criminal damage and thefts of and from motor vehicles. All of that offer the potential for glass fragments to be transferred from anything made of glass which breaks, to whoever or whatever was responsible. Variation in manufacture of glass allows considerable discrimination even with tiny fragments. In this study, we worked glass (...) and testing of artificial neural network model created by the JustNN. The aim of the study is help investigator in identifying the type of glass found in arena of the crime. The Neural Network model was trained and validated using the type of glass dataset. The accuracy of model in predicting the type of glass reached 96.7%. Thus neural network is suitable for predicating type of glasses. (shrink)
    Download  
     
    Export citation  
     
    Bookmark   28 citations  
  9. Classification of Global Catastrophic Risks Connected with Artificial Intelligence.Alexey Turchin & David Denkenberger - 2020 - AI and Society 35 (1):147-163.
    A classification of the global catastrophic risks of AI is presented, along with a comprehensive list of previously identified risks. This classification allows the identification of several new risks. We show that at each level of AI’s intelligence power, separate types of possible catastrophes dominate. Our classification demonstrates that the field of AI risks is diverse, and includes many scenarios beyond the commonly discussed cases of a paperclip maximizer or robot-caused unemployment. Global catastrophic failure could happen at (...)
    Download  
     
    Export citation  
     
    Bookmark   10 citations  
  10. Classification of Real and Fake Human Faces Using Deep Learning.Fatima Maher Salman & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):1-14.
    Artificial intelligence (AI), deep learning, machine learning and neural networks represent extremely exciting and powerful machine learning-based techniques used to solve many real-world problems. Artificial intelligence is the branch of computer sciences that emphasizes the development of intelligent machines, thinking and working like humans. For example, recognition, problem-solving, learning, visual perception, decision-making and planning. Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Deep learning (...)
    Download  
     
    Export citation  
     
    Bookmark   26 citations  
  11. Classification, Kinds, Taxonomic Stability, and Conceptual Change.Jaipreet Mattu & Jacqueline Anne Sullivan - forthcoming - Aggression and Violent Behavior.
    Scientists represent their world, grouping and organizing phenomena into classes by means of concepts. Philosophers of science have historically been interested in the nature of these concepts, the criteria that inform their application and the nature of the kinds that the concepts individuate. They also have sought to understand whether and how different systems of classification are related and more recently, how investigative practices shape conceptual development and change. Our aim in this paper is to provide a critical overview (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  12. Causal classification of diseases.Andrej Poleev - 2020 - Enzymes.
    „Errors are the greatest obstacles to the progress of science; to correct such errors is of more practical value than to achieve new knowledge,“ asserted Eugen Bleuler. Basic error of several prevailing classification schemes of pathological conditions, as for example ICD-10, lies in confusing and mixing symptoms with diseases, what makes them unscientific. Considering the need to bring order into the chaos and light into terminological obscureness, I introduce the Causal classification of diseases originating from the notion of (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  13. A classification system for argumentation schemes.Douglas Walton & Fabrizio Macagno - 2016 - Argument and Computation 6 (3):219-245.
    This paper explains the importance of classifying argumentation schemes, and outlines how schemes are being used in current research in artificial intelligence and computational linguistics on argument mining. It provides a survey of the literature on scheme classification. What are so far generally taken to represent a set of the most widely useful defeasible argumentation schemes are surveyed and explained systematically, including some that are difficult to classify. A new classification system covering these centrally important schemes is built.
    Download  
     
    Export citation  
     
    Bookmark   11 citations  
  14. Classification of Sign-Language Using MobileNet - Deep Learning.Tanseem N. Abu-Jamie & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (7):29-40.
    Abstract: Sign language recognition is one of the most rapidly expanding fields of study today. Many new technologies have been developed in recent years in the fields of artificial intelligence the sign language-based communication is valuable to not only deaf and dumb community, but also beneficial for individuals suffering from Autism, downs Syndrome, Apraxia of Speech for correspondence. The biggest problem faced by people with hearing disabilities is the people's lack of understanding of their requirements. In this paper we try (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  15. Classification of plant Species Using Neural Network.Muhammad Ashraf Al-Azbaki, Mohammed S. Abu Nasser, Mohammed A. Hasaballah & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (10):28-35.
    Abstract: In this study, we explore the possibility of classifying the plant species. We collected the plant species from Kaggle website. This dataset encompasses 544 samples, encompassing 136 distinct plant species. Recent advancements in machine learning, particularly Artificial Neural Networks (ANNs), offer promise in enhancing plant Species classification accuracy and efficiency. This research explores plant Species classification, harnessing neural networks' power. Utilizing a rich dataset from Kaggle, containing 544 entries, we develop and evaluate a neural network model. Our (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  16. A classification system for argumentation schemes.Douglas Walton & Fabrizio Macagno - 2015 - Argument and Computation 6 (3):219-245.
    This paper explains the importance of classifying argumentation schemes, and outlines how schemes are being used in current research in artificial intelligence and computational linguistics on argument mining. It provides a survey of the literature on scheme classification. What are so far generally taken to represent a set of the most widely useful defeasible argumentation schemes are surveyed and explained systematically, including some that are difficult to classify. A new classification system covering these centrally important schemes is built.
    Download  
     
    Export citation  
     
    Bookmark   13 citations  
  17.  27
    Classification of Rice Using Deep Learning.Mohammed H. S. Abueleiwa & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):26-36.
    Abstract: Rice is one of the most important staple crops in the world and serves as a staple food for more than half of the global population. It is a critical source of nutrition, providing carbohydrates, vitamins, and minerals to millions of people, particularly in Asia and Africa. This paper presents a study on using deep learning for the classification of different types of rice. The study focuses on five specific types of rice: Arborio, Basmati, Ipsala, Jasmine, and Karacadag. (...)
    Download  
     
    Export citation  
     
    Bookmark  
  18. Defeasible Classifications and Inferences from Definitions.Fabrizio Macagno & Douglas Walton - 2010 - Informal Logic 30 (1):34-61.
    We contend that it is possible to argue reasonably for and against arguments from classifications and definitions, provided they are seen as defeasible (subject to exceptions and critical questioning). Arguments from classification of the most common sorts are shown to be based on defeasible reasoning of various kinds represented by patterns of logical reasoning called defeasible argumentation schemes. We show how such schemes can be identified with heuristics, or short-cut solutions to a problem. We examine a variety of arguments (...)
    Download  
     
    Export citation  
     
    Bookmark   14 citations  
  19. Classification of Sign-language Using VGG16.Tanseem N. Abu-Jamie & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (6):36-46.
    Sign Language Recognition (SLR) aims to translate sign language into text or speech in order to improve communication between deaf-mute people and the general public. This task has a large social impact, but it is still difficult due to the complexity and wide range of hand actions. We present a novel 3D convolutional neural network (CNN) that extracts discriminative spatial-temporal features from photo datasets. This article is about classification of sign languages are not universal and are usually not mutually (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  20. Interactive Classification and Practice in the Social Sciences.Matt L. Drabek - 2010 - Poroi 6 (2):62-80.
    This paper examines the ways in which social scientific discourse and classification interact with the objects of social scientific investigation. I examine this interaction in the context of the traditional philosophical project of demarcating the social sciences from the natural sciences. I begin by reviewing Ian Hacking’s work on interactive classification and argue that there are additional forms of interaction that must be treated.
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  21.  85
    A classification system for argumentation schemes.Douglas Walton & Fabrizio Macagno - 2015 - Argument and Computation 6 (3):219-245.
    This paper explains the importance of classifying argumentation schemes, and outlines how schemes are being used in current research in artificial intelligence and computational linguistics on argument mining. It provides a survey of the literature on scheme classification. What are so far generally taken to represent a set of the most widely useful defeasible argumentation schemes are surveyed and explained systematically, including some that are difficult to classify. A new classification system covering these centrally important schemes is built.
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  22. Reasoning from Classifications and Definitions.Douglas Walton & Fabrizio Macagno - 2009 - Argumentation 23 (1):81-107.
    In this paper we analyze the uses and misuses of argumentation schemes from verbal classification, and show how argument from definition supports argumentation based on argument from verbal classification. The inquiry has inevitably included the broader study of the concept of definition. The paper presents the schemes for argument from classification and for argument from definition, and shows how the latter type of argument so typically supports the former. The problem of analyzing arguments based on classification (...)
    Download  
     
    Export citation  
     
    Bookmark   14 citations  
  23. Disagreement & classification in comparative cognitive science.Alexandria Boyle - forthcoming - Noûs.
    Comparative cognitive science often involves asking questions like ‘Do nonhumans have C?’ where C is a capacity we take humans to have. These questions frequently generate unproductive disagreements, in which one party affirms and the other denies that nonhumans have the relevant capacity on the basis of the same evidence. I argue that these questions can be productively understood as questions about natural kinds: do nonhuman capacities fall into the same natural kinds as our own? Understanding such questions in this (...)
    Download  
     
    Export citation  
     
    Bookmark  
  24. Racial Classification Without Race: Edwards’ Fallacy.Adam Hochman - 2021 - In Lorusso Ludovica & Winther Rasmus (eds.), Remapping Race in a Global Context. Routledge. pp. 74–91.
    A. W. F. Edwards famously named “Lewontin’s fallacy” after Richard Lewontin, the geneticist who showed that most human genetic diversity can be found within any given racialized group. “Lewontin’s fallacy” is the assumption that uncorrelated genetic data would be sufficient to classify genotypes into conventional “racial” groups. In this chapter, I argue that Lewontin does not commit the fallacy named after him, and that it is not a genuine fallacy. Furthermore, I argue that when Edwards assumes that stable classification (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  25.  29
    Fish Classification Using Deep Learning.M. N. Ayyad & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):51-58.
    Abstract: Fish are important for both nutritional and economic reasons. They are a good source of protein, vitamins, and minerals and play a significant role in human diets, especially in coastal and island communities. In addition, fishing and fish farming are major industries that provide employment and income for millions of people worldwide. Moreover, fish play a critical role in marine ecosystems, serving as prey for larger predators and helping to maintain the balance of aquatic food chains. Overall, fish play (...)
    Download  
     
    Export citation  
     
    Bookmark  
  26. Classification of Age and Gender Using ResNet - Deep Learning.Aysha I. Mansour & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (8):20-29.
    Age and gender classification has become relevant to an increasing amount of applications, particularly since the rise of social platforms and social media. Even Nevertheless, contrast to the large performance improvements recently reported for the closely related task of audio. In this research, we show that performance on these tasks can be significantly improved by learning representations using deep convolutional neural networks (CNN). where we get in the ResNet the training accuracy was 98% ,validation accuracy 95%, testing accuracy 96% (...)
    Download  
     
    Export citation  
     
    Bookmark  
  27. Psychiatric classification and diagnosis. Delusions and confabulations.Lisa Bortolotti - 2011 - Paradigmi (1):99-112.
    In psychiatry some disorders of cognition are distinguished from instances of normal cognitive functioning and from other disorders in virtue of their surface features rather than in virtue of the underlying mechanisms responsible for their occurrence. Aetiological considerations often cannot play a significant classificatory and diagnostic role, because there is no sufficient knowledge or consensus about the causal history of many psychiatric disorders. Moreover, it is not always possible to uniquely identify a pathological behaviour as the symptom of a certain (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  28. Classification of Sign-Language Using Deep Learning by ResNet.Tanseem N. Abu-Jamie & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (8):25-34.
    American Sign Language, or ASL as its acronym is commonly known, is a fascinating language, and many people outside of the Deaf community have begun to recognize its value and purpose. It is a visual language consisting of coordinated hand gestures, body movements, and facial expressions. Sign language is not a universal language; it varies by country and is heavily influenced by the native language and culture. The American Sign Language alphabet and the British Sign Language alphabet are completely contrary. (...)
    Download  
     
    Export citation  
     
    Bookmark  
  29. Classification of Sign-Language Using Deep Learning - A Comparison between Inception and Xception models.Tanseem N. Abu-Jamie & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (8):9-19.
    there is a communication gap between hearing-impaired people and those with normal hearing, sign language is the main means of communication in the hearing-impaired population. Continuous sign language recognition, which can close the communication gap, is a difficult task since the ordered annotations are weakly supervised and there is no frame-level label. To solve this issue, we compare the accuracy of each model using two deep learning models, Inception and Xception . To that end, the purpose of this paper is (...)
    Download  
     
    Export citation  
     
    Bookmark  
  30. Type of Tomato Classification Using Deep Learning.Mahmoud A. Alajrami & Samy S. Abu-Naser - 2020 - International Journal of Academic Pedagogical Research (IJAPR) 3 (12):21-25.
    Abstract: Tomatoes are part of the major crops in food security. Tomatoes are plants grown in temperate and hot regions of South American origin from Peru, and then spread to most countries of the world. Tomatoes contain a lot of vitamin C and mineral salts, and are recommended for people with constipation, diabetes and patients with heart and body diseases. Studies and scientific studies have proven the importance of eating tomato juice in reducing the activity of platelets in diabetics, which (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  31. Classifications of Pineapple using Deep Learning.Amjad H. Alfarra, Lamis F. Samhan, Yasmin E. Aslem, Marah M. Almasawabe & Samy S. Abu-Naser - 2021 - International Journal of Academic Information Systems Research (IJAISR) 5 (12):37-41.
    A pineapple is a tropical plant with eatable leafy foods most monetarily critical plant in the family Bromeliaceous. The pineapple is native to South America, where it has been developed for a long time. The acquaintance of the pineapple with Europe in the seventeenth century made it a critical social symbol of extravagance. Since the 1820s, pineapple has been industrially filled in nurseries and numerous tropical manors. Further, it is the third most significant tropical natural product in world creation. In (...)
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  32.  21
    Vegetable Classification Using Deep Learning.Mostafa El-Ghoul & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):105-112.
    Abstract: Vegetables are an essential component of a healthy diet and play a critical role in promoting overall health and well- being. Vegetables are rich in important vitamins and minerals, including vitamin C, folate, potassium, and iron. They also provide fiber, which helps maintain digestive health and prevent chronic diseases. We are proposing a deep learning model for the classification of vegetables. A dataset was collected from Kaggle depository for Vegetable with 15000 images for 15 different classes. The data (...)
    Download  
     
    Export citation  
     
    Bookmark  
  33.  22
    Classification of Chicken Diseases Using Deep Learning.Mohammed Al Qatrawi & Samy S. Abu-Naser - 2024 - Information Journal of Academic Information Systems Research (Ijaisr) 8 (4):9-17.
    Abstract: In recent years, the outbreak of various poultry diseases has posed a significant threat to the global poultry industry. Therefore, the accurate and timely detection of chicken diseases is critical to reduce economic losses and prevent the spread of diseases. In this study, we propose a method for classifying chicken diseases using a convolutional neural network (CNN). The proposed method involves preprocessing the chicken images, building and training a CNN model, and evaluating the performance of the model. The dataset (...)
    Download  
     
    Export citation  
     
    Bookmark  
  34.  40
    Classification of Apple Diseases Using Deep Learning.Ola I. A. Lafi & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):1-9.
    Abstract: In this study, we explore the challenge of identifying and preventing diseases in apple trees, which is a popular activity but can be difficult due to the susceptibility of these trees to various diseases. To address this challenge, we propose the use of Convolutional Neural Networks, which have proven effective in automatically detecting plant diseases. To validate our approach, we use images of apple leaves, including Apple Rot Leaves, Leaf Blotch, Healthy Leaves, and Scab Leaves collected from Kaggle which (...)
    Download  
     
    Export citation  
     
    Bookmark  
  35. The classifications of living beings.Peter Heuer & Boris Hennig - 2008 - In Peter Heuer & Boris Hennig (eds.), Applied Ontology. pp. 197--217.
    This chapter proceeds in five steps. First, we will describe and justify the structure of the traditional system of species classification. Second, we will discuss three formal principles governing the development of taxonomies in general. It will emerge that, in addition to these formal principles, a division of living beings must meet certain empirical constraints. In the third section, we will show that the traditional division of living beings into species best meets these constraints. Fourth, we will argue that (...)
    Download  
     
    Export citation  
     
    Bookmark  
  36. The Classification, Definition, and Ontology of Delusion.José Eduardo Porcher - 2016 - Revista Latinoamericana de Psicopatología Fundamental 19 (1):167-181.
    Although delusion is one of the central concepts of psychopathology, it stills eludes precise conceptualization. In this paper, I present certain basic issues concerning the classification and definition of delusion, as well as its ontological status. By examining these issues, I aim to shed light on the ambiguity of the clinical term ‘delusion’ and its extension, as well as provide clues as to why philosophers are increasingly joining the ranks of psychiatrists, psychologists, and neuroscientists in the effort to come (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  37. Papaya Maturity Classifications using Deep Convolutional Neural Networks.Marah M. Al-Masawabe, Lamis F. Samhan, Amjad H. AlFarra, Yasmeen E. Aslem & Samy S. Abu-Naser - 2021 - International Journal of Engineering and Information Systems (IJEAIS) 5 (12):60-67.
    Papaya is a tropical fruit with a green cover, yellow pulp, and a taste between mango and cantaloupe, having commercial importance because of its high nutritive and medicinal value. The process of sorting papaya fruit based on maturely is one of the processes that greatly determine the mature of papaya fruit that will be sold to consumers. The manual grading of papaya fruit based on human visual perception is time-consuming and destructive. The objective of this paper is to the status (...)
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  38. Classification and Ambiguity: the Role of Definition in a Conceptual System.Douglas Walton & Fabrizio Macagno - 2009 - Studies in Logic, Grammar and Rhetoric 16 (29).
    With the advent of the semantic web, the problem of ambiguity is becoming more and more urging. Semantic analysis is necessary for explaining and resolving some sorts of ambiguity by inquiring into the relation between possibilities of predication and definition of a concept in order to solve problems such as interpretation and ambiguity. If computing is now approaching such problems of linguistic analysis, what is worth inquiring into is how the development of linguistic studies can be useful for developing the (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  39. Availability classification for applications in construction production system: A review.Milan Mirkovic - 2019 - Facta Universitatis, Series: Linguistics and Literature 17 (1):1-17.
    The aim of the paper is to improve availability classifications of components for application in construction systems. Construction production systems belong to project-based systems with serial-parallel structures with or without redundant components, and the availability function has a significant impact on the performance indicators of components and systems. The main indicators of function of the components are the availability, capacity, costs, and project time. A new approach to classification makes it possible to choose the most appropriate methodology for assessing (...)
    Download  
     
    Export citation  
     
    Bookmark  
  40. Classification of Disjunctivism about the Phenomenology of Visual Experience.Takuya Niikawa - 2019 - Journal of Philosophical Research 44:89-110.
    This paper proposes a classificatory framework for disjunctivism about the phenomenology of visual perceptual experience. Disjunctivism of this sort is typically divided into positive and negative disjunctivism. This distinction successfully reflects the disagreement amongst disjunctivists regarding the explanatory status of the introspective indiscriminability of veridical perception and hallucination. However, it is unsatisfactory in two respects. First, it cannot accommodate eliminativism about the phenomenology of hallucination. Second, the class of positive disjunctivism is too coarse-grained to provide an informative overview of the (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  41. Phenomenological Psychopathology and Psychiatric Classification.Anthony Vincent Fernandez - 2018 - In Giovanni Stanghellini, Matthew Broome, Anthony Vincent Fernandez, Paolo Fusar-Poli, Andrea Raballo & René Rosfort (eds.), The Oxford Handbook of Phenomenological Psychopathology. Oxford: Oxford University Press. pp. 1016-1030.
    In this chapter, I provide an overview of phenomenological approaches to psychiatric classification. My aim is to encourage and facilitate philosophical debate over the best ways to classify psychiatric disorders. First, I articulate phenomenological critiques of the dominant approach to classification and diagnosis—i.e., the operational approach employed in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and the International Classification of Diseases (ICD-10). Second, I describe the type or typification approach to psychiatric classification, which I (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  42.  28
    Classification by decomposition: a novel approach to classification of symmetric $$2\times 2$$ games.Mikael Böörs, Tobias Wängberg, Tom Everitt & Marcus Hutter - 2022 - Theory and Decision 93 (3):463-508.
    In this paper, we provide a detailed review of previous classifications of 2 × 2 games and suggest a mathematically simple way to classify the symmetric 2 × 2 games based on a decomposition of the payoff matrix into a cooperative and a zero-sum part. We argue that differences in the interaction between the parts is what makes games interesting in different ways. Our claim is supported by evolutionary computer experiments and findings in previous literature. In addition, we provide a (...)
    Download  
     
    Export citation  
     
    Bookmark  
  43. The Classification of the Sciences and Cross-disciplinarity.Jaime Nubiola - 2005 - Transactions of the Charles S. Peirce Society 41 (2):271-282.
    In a world of ever growing specialization, the idea of a unity of science is commonly discarded, but cooperative work involving cross-disciplinary points of view is encouraged. The aim of this paper is to show with some textual support that Charles S. Peirce not only identified this paradoxical situation a century ago, but he also mapped out some paths for reaching a successful solution. A particular attention is paid to Peirce's classification of the sciences and to his conception of (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  44. Classification of Alzheimer’s Disease Using Traditional Classifiers with Pre-Trained CNN.Husam R. Almadhoun & Samy S. Abu-Naser - 2021 - International Journal of Academic Health and Medical Research (IJAHMR) 5 (4):17-21.
    Abstract: Alzheimer's disease (AD) is one of the most common types of dementia. Symptoms appear gradually and end with severe brain damage. People with Alzheimer's disease lose the abilities of knowledge, memory, language and learning. Recently, the classification and diagnosis of diseases using deep learning has emerged as an active topic covering a wide range of applications. This paper proposes examining abnormalities in brain structures and detecting cases of Alzheimer's disease especially in the early stages, using features derived from (...)
    Download  
     
    Export citation  
     
    Bookmark  
  45. Philosophy of Science, Psychiatric Classification, and the DSM.Jonathan Y. Tsou - 2019 - In Bluhm Robyn & Tekin Serife (eds.), The Bloomsbury Companion to Philosophy of Psychiatry. Bloomsbury. pp. 177-196.
    This chapter examines philosophical issues surrounding the classification of mental disorders by the Diagnostic and Statistical Manual of Mental Disorders (DSM). In particular, the chapter focuses on issues concerning the relative merits of descriptive versus theoretical approaches to psychiatric classification and whether the DSM should classify natural kinds. These issues are presented with reference to the history of the DSM, which has been published regularly by the American Psychiatric Association since 1952 and is currently in its fifth edition. (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  46. On Triplet Classification of Concepts.Vladimir Kuznetsov - 1997 - Knowledge Organization 24 (3):163-175.
    The scheme for classifications of concepts is introduced. It has founded on the triplet model of concepts. In this model a concept is depicted by means of three kinds of knowledge: a concept base, a concept representing part and the linkage between them. The idea of triplet classifications of concepts is connected with a usage of various specifications of these knowledge kinds as classification criteria.
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  47.  26
    Classification of Dates Using Deep Learning.Raed Z. Sababa & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):18-25.
    Abstract: Dates are the fruit of date palm trees, and it is one of the fruits famous for its high nutritional value. It is a summer fruit spread in the Arab world. In the past, the Arabs relied on it in their daily lives. Dates take an oval shape and vary in size from 20 to 60 mm in length and 8 to 30 mm in diameter. The ripe fruit consists of a hard core surrounded by a papery cover called (...)
    Download  
     
    Export citation  
     
    Bookmark  
  48.  22
    Tomato Leaf Diseases Classification using Deep Learning.Mohammed F. El-Habibi & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):73-80.
    Abstract: Tomatoes are among the most popular vegetables in the world due to their frequent use in many dishes, which fall into many varieties in common and traditional foods, and due to their rich ingredients such as vitamins and minerals, so they are frequently used on a daily basis, When we focus our attention on this vegetable, we must also focus and take into consideration the diseases that affect this vegetable, a deep learning model that classifies tomato diseases has been (...)
    Download  
     
    Export citation  
     
    Bookmark  
  49. Causation and melanoma classification.Brendan Clarke - 2011 - Theoretical Medicine and Bioethics 32 (1):19-32.
    In this article, I begin by giving a brief history of melanoma causation. I then discuss the current manner in which malignant melanoma is classified. In general, these systems of classification do not take account of the manner of tumour causation. Instead, they are based on phenomenological features of the tumour, such as size, spread, and morphology. I go on to suggest that misclassification of melanoma is a major problem in clinical practice. I therefore outline an alternative means of (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  50. Natural Kinds, Psychiatric Classification and the History of the DSM.Jonathan Y. Tsou - 2016 - History of Psychiatry 27 (4):406-424.
    This paper addresses philosophical issues concerning whether mental disorders are natural kinds and how the DSM should classify mental disorders. I argue that some mental disorders (e.g., schizophrenia, depression) are natural kinds in the sense that they are natural classes constituted by a set of stable biological mechanisms. I subsequently argue that a theoretical and causal approach to classification would provide a superior method for classifying natural kinds than the purely descriptive approach adopted by the DSM since DSM-III. My (...)
    Download  
     
    Export citation  
     
    Bookmark   19 citations  
1 — 50 / 697