Results for 'cognitivism, emergence, enactive approach, Buddhism, no-self, mindfulness, neural networks, self-organization, unsupervised learning'

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  1. Book Review of "The Embodied Mind: Cognitive Science and Human Experience". [REVIEW]Anand Rangarajan - manuscript
    This is an in-depth review of "The Embodied Mind: Cognitive Science and Human Experience" by Francisco Varela, Evan Thompson and Eleanor Rosch.
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  2. Evolving Self-taught Neural Networks: The Baldwin Effect and the Emergence of Intelligence.Nam Le - 2019 - In AISB Annual Convention 2019 -- 10th Symposium on AI & Games.
    The so-called Baldwin Effect generally says how learning, as a form of ontogenetic adaptation, can influence the process of phylogenetic adaptation, or evolution. This idea has also been taken into computation in which evolution and learning are used as computational metaphors, including evolving neural networks. This paper presents a technique called evolving self-taught neural networks – neural networks that can teach themselves without external supervision or reward. The self-taught neural network is intrinsically (...)
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  3. Seven properties of self-organization in the human brain.Birgitta Dresp-Langley - 2020 - Big Data and Cognitive Computing 2 (4):10.
    The principle of self-organization has acquired a fundamental significance in the newly emerging field of computational philosophy. Self-organizing systems have been described in various domains in science and philosophy including physics, neuroscience, biology and medicine, ecology, and sociology. While system architecture and their general purpose may depend on domain-specific concepts and definitions, there are (at least) seven key properties of self-organization clearly identified in brain systems: 1) modular connectivity, 2) unsupervised learning, 3) adaptive ability, 4) (...)
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  4. A Mindful Bypassing: Mindfulness, Trauma and the Buddhist Theory of No-Self.Julien Tempone-Wiltshire & Traill Dowie - 2024 - Journal of the Oxford Centre for Buddhist Studies 23 (1):149-174.
    This article examines the Buddhist idea of anātman, ‘no- self ’ and pudgala, ‘the person’ in relation to the notion of ‘self ’ emerging from contemporary cognitive science. The Buddhist no-self doctrine is enriched by the cognitive scientist’s understanding of the multiple facets of selfhood, or structures of experience, and the causative action of a functional self in the world. A proper understanding of the Buddhist concepts of anātman and pudgala proves critical to mindfulness-based therapeutic interventions: (...)
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  5. Human Symmetry Uncertainty Detected by a Self-Organizing Neural Network Map.Birgitta Dresp-Langley - 2021 - Symmetry 13:299.
    Symmetry in biological and physical systems is a product of self-organization driven by evolutionary processes, or mechanical systems under constraints. Symmetry-based feature extraction or representation by neural networks may unravel the most informative contents in large image databases. Despite significant achievements of artificial intelligence in recognition and classification of regular patterns, the problem of uncertainty remains a major challenge in ambiguous data. In this study, we present an artificial neural network that detects symmetry uncertainty states in human (...)
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  6. Remarks on the Geometry of Complex Systems and Self-Organization.Luciano Boi - 2012 - In Vincenzo Fano, Enrico Giannetto, Giulia Giannini & Pierluigi Graziani (eds.), Complessità e Riduzionismo. © ISONOMIA – Epistemologica, University of Urbino. pp. 28-43.
    Let us start by some general definitions of the concept of complexity. We take a complex system to be one composed by a large number of parts, and whose properties are not fully explained by an understanding of its components parts. Studies of complex systems recognized the importance of “wholeness”, defined as problems of organization (and of regulation), phenomena non resolvable into local events, dynamics interactions in the difference of behaviour of parts when isolated or in higher configuration, etc., in (...)
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  7. Streamlined Book Rating Prediction with Neural Networks.Lana Aarra, Mohammed S. Abu Nasser, Mohammed A. Hasaballah & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (10):7-13.
    Abstract: Online book review platforms generate vast user data, making accurate rating prediction crucial for personalized recommendations. This research explores neural networks as simple models for predicting book ratings without complex algorithms. Our novel approach uses neural networks to predict ratings solely from user-book interactions, eliminating manual feature engineering. The model processes data, learns patterns, and predicts ratings. We discuss data preprocessing, neural network design, and training techniques. Real-world data experiments show the model's effectiveness, surpassing traditional methods. (...)
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  8.  17
    Criticism of individualist and collectivist methodological approaches to social emergence.S. M. Reza Amiri Tehrani - 2023 - Expositions: Interdisciplinary Studies in the Humanities 15 (3):111-139.
    ABSTRACT The individual-community relationship has always been one of the most fundamental topics of social sciences. In sociology, this is known as the micro-macro relationship while in economics it refers to the processes, through which, individual actions lead to macroeconomic phenomena. Based on philosophical discourse and systems theory, many sociologists even use the term "emergence" in their understanding of micro-macro relationship, which refers to collective phenomena that are created by the cooperation of individuals, but cannot be reduced to individual actions. (...)
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  9. Insight and the no‐self in deep brain stimulation.Laura Specker Sullivan - 2018 - Bioethics 33 (4):487-494.
    Ethical analyses of the effects of neural interventions commonly focus on changes to personality and behavior, interpreting these changes in terms of authenticity and identity. These phenomena have led to debate among ethicists about the meaning of these terms for ethical analysis of such interventions. While these theoretical approaches have different criteria for ethical significance, they agree that patients’ reports are concerning because a sense of self is valuable. In this paper, I question this assumption. I propose that (...)
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  10. Scientism, Philosophy and Brain-Based Learning.Gregory M. Nixon - 2013 - Northwest Journal of Teacher Education 11 (1):113-144.
    [This is an edited and improved version of "You Are Not Your Brain: Against 'Teaching to the Brain'" previously published in *Review of Higher Education and Self-Learning* 5(15), Summer 2012.] Since educators are always looking for ways to improve their practice, and since empirical science is now accepted in our worldview as the final arbiter of truth, it is no surprise they have been lured toward cognitive neuroscience in hopes that discovering how the brain learns will provide a (...)
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  11. Networks of Gene Regulation, Neural Development and the Evolution of General Capabilities, Such as Human Empathy.Alfred Gierer - 1998 - Zeitschrift Für Naturforschung C - A Journal of Bioscience 53:716-722.
    A network of gene regulation organized in a hierarchical and combinatorial manner is crucially involved in the development of the neural network, and has to be considered one of the main substrates of genetic change in its evolution. Though qualitative features may emerge by way of the accumulation of rather unspecific quantitative changes, it is reasonable to assume that at least in some cases specific combinations of regulatory parts of the genome initiated new directions of evolution, leading to novel (...)
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  12.  66
    The Self as the Personal Scapegoat of Chinese and Japanese Buddhism: A Comparative Analysis and Treatise on the Universal Manifestation of the Christ Figure.Asher Zachman - manuscript
    In this paper, I elucidate the scapegoat construct and its necessary psychological presence within theistic and atheistic variations of the narrative self, as well as the Chinese and Japanese variations of the Buddhist no-self, and enumerate the ritual processes undertaken by these practitioners to create, banish, and sacrifice their respective motifs of applied blame. I attempt to substantiate the inward and outward transcendent manifestations of this construct as the identifying qualities of the Christ figure, and the harmful external (...)
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  13. The Self-Field: Mind, Body and Environment.Chris Abel - 2021 - Oxford: Routledge.
    In this incisive study of the biological and cultural origins of the human self, the author challenges readers to re-think ideas about the self and consciousness as being exclusive to humans. In their place, he expounds a metatheoretical approach to the self as a purposeful system of extended cognition common to animal life: the invisible medium maintaining mind, body and environment as an integrated 'field of being'. Supported by recent research in evolutionary and developmental studies together with (...)
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  14. Connectionist models of mind: scales and the limits of machine imitation.Pavel Baryshnikov - 2020 - Philosophical Problems of IT and Cyberspace 2 (19):42-58.
    This paper is devoted to some generalizations of explanatory potential of connectionist approaches to theoretical problems of the philosophy of mind. Are considered both strong, and weaknesses of neural network models. Connectionism has close methodological ties with modern neurosciences and neurophilosophy. And this fact strengthens its positions, in terms of empirical naturalistic approaches. However, at the same time this direction inherits weaknesses of computational approach, and in this case all system of anticomputational critical arguments becomes applicable to the connectionst (...)
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  15. Complexity Reality and Scientific Realism.Avijit Lahiri - manuscript
    We introduce the notion of complexity, first at an intuitive level and then in relatively more concrete terms, explaining the various characteristic features of complex systems with examples. There exists a vast literature on complexity, and our exposition is intended to be an elementary introduction, meant for a broad audience. -/- Briefly, a complex system is one whose description involves a hierarchy of levels, where each level is made of a large number of components interacting among themselves. The time evolution (...)
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  16. Learning to Communicate: The Emergence of Signaling in Spatialized Arrays of Neural Nets.Patrick Grim, Trina Kokalis & Paul St Denis - 2003 - Adaptive Behavior 10:45-70.
    We work with a large spatialized array of individuals in an environment of drifting food sources and predators. The behavior of each individual is generated by its simple neural net; individuals are capable of making one of two sounds and are capable of responding to sounds from their immediate neighbors by opening their mouths or hiding. An individual whose mouth is open in the presence of food is “fed” and gains points; an individual who fails to hide when a (...)
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  17. Brains Emerging: On Modularity and Self-organisation of Neural Development In Vivo and In Vitro.Paul Gottlob Layer - 2019 - In Lars H. Wegner & Ulrich Lüttge (eds.), Emergence and Modularity in Life Sciences. Springer Verlag. pp. 145-169.
    Molecular developmental biology has expanded our conceptions of gene actions, underpinning that embryonic development is not only governed by a set of specific genes, but as much by space–time conditions of its developing modules. Typically, formation of cellular spheres, their transformation into planar epithelia, followed by tube formations and laminations are modular steps leading to the development of nervous tissues. Thereby, actions of organising centres, morphogenetic movements, inductive events between epithelia, tissue polarity reversal, widening of epithelia, and all these occurring (...)
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  18. Neurodemocracy: Self-Organization of the Embodied Mind.Linus Huang - 2017 - Dissertation, University of Sydney
    This thesis contributes to a better conceptual understanding of how self-organized control works. I begin by analyzing the control problem and its solution space. I argue that the two prominent solutions offered by classical cognitive science (centralized control with rich commands, e.g., the Fodorian central systems) and embodied cognitive science (distributed control with simple commands, such as the subsumption architecture by Rodney Brooks) are merely two positions in a two-dimensional solution space. I outline two alternative positions: one is distributed (...)
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  19. Insight Knowledge of No Self in Buddhism: An Epistemic Analysis.Miri Albahari - 2014 - Philosophers' Imprint 14.
    Imagine a character, Mary Analogue, who has a complete theoretical knowledge of her subject matter: the illusory nature of self. Suppose that when presenting her paper on no self at a conference she suffers stage-fright – a reaction that implies she is under an illusion of the very self whose existence she denies. Might there be something defective about her knowledge of no self? The Buddhist tradition would claim that Mary Analogue, despite her theoretical omniscience, lacks (...)
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  20. The trans-species core SELF: the emergence of active cultural and neuro-ecological agents through self-related processing within subcortical-cortical midline networks.Jaak Panksepp & Georg Northoff - 2009 - Consciousness and Cognition 18 (1):193–215.
    The nature of “the self” has been one of the central problems in philosophy and more recently in neuroscience. This raises various questions: Can we attribute a self to animals? Do animals and humans share certain aspects of their core selves, yielding a trans-species concept of self? What are the neural processes that underlie a possible trans-species concept of self? What are the developmental aspects and do they result in various levels of self-representation? Drawing (...)
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  21. From Biological Synapses to "Intelligent" Robots.Birgitta Dresp-Langley - 2022 - Electronics 11:1-28.
    This selective review explores biologically inspired learning as a model for intelligent robot control and sensing technology on the basis of specific examples. Hebbian synaptic learning is discussed as a functionally relevant model for machine learning and intelligence, as explained on the basis of examples from the highly plastic biological neural networks of invertebrates and vertebrates. Its potential for adaptive learning and control without supervision, the generation of functional complexity, and control architectures based on (...)-organization is brought forward. Learning without prior knowledge based on excitatory and inhibitory neural mechanisms accounts for the process through which survival-relevant or task-relevant representations are either reinforced or suppressed. The basic mechanisms of unsupervised biological learning drive synaptic plasticity and adaptation for behavioral success in living brains with different levels of complexity. The insights collected here point toward the Hebbian model as a choice solution for “intelligent” robotics and sensor systems. Keywords: Hebbian learning; synaptic plasticity; neural networks; self-organization; brain; reinforcement; sensory processing; robot control . (shrink)
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  22. Constructivist Learning Amid the COVID-19 Pandemic: Investigating Students’ Perceptions of Biology Self-Learning Modules.Aaron Funa & Frederick Talaue - 2021 - International Journal of Learning, Teaching and Educational Research 20 (3):250-264.
    Modes of teaching and learning have had to rapidly shift amid the COVID-19 pandemic. As an emergency response, students from Philippine public schools were provided learning modules based on a minimized list of essential learning competencies in Biology. Using a cross-sectional survey method, we investigated students’ perceptions of the Biology self-learning modules (BSLM) that were designed in print and digitized formats according to a constructivist learning approach. Senior high school STEM students from grades 11 (...)
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  23. Are self-organizing biochemical networks emergent?Christophe Malaterre - 2009 - In Maryvonne Gérin & Marie-Christine Maurel (eds.), Origins of Life: Self-Organization and/or Biological Evolution? EDP Sciences. pp. 117--123.
    Biochemical networks are often called upon to illustrate emergent properties of living systems. In this contribution, I question such emergentist claims by means of theoretical work on genetic regulatory models and random Boolean networks. If the existence of a critical connectivity Kc of such networks has often been coined “emergent” or “irreducible”, I propose on the contrary that the existence of a critical connectivity Kc is indeed mathematically explainable in network theory. This conclusion also applies to many other types of (...)
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  24. Emergent Sign-Action.Pedro Atã & João Queiroz - 2019 - European Journal of Pragmatism and American Philosophy 11 (2).
    We explore Peirce’s pragmatic conception of sign action, as a distributed and emergent view of cognition and exemplify with the emergence of classical ballet. In our approach, semiosis is a temporally distributed process in which a regular tendency towards certain future outcomes emerges out of a history of sign actions. Semiosis self-organizes in time, in a process that continuously entails the production of more signs. Emergence is a ubiquitous condition in this process: the translation of signs into signs cannot (...)
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  25. Lost in the socially extended mind: Genuine intersubjectivity and disturbed self-other demarcation in schizophrenia.Tom Froese & Joel Krueger - 2020 - In Christian Tewes & Giovanni Stanghellini (eds.), Time and Body: Phenomenological and Psychopathological Approaches. New York, NY: Cambridge University Press. pp. 318-340.
    Much of the characteristic symptomatology of schizophrenia can be understood as resulting from a pervasive sense of disembodiment. The body is experienced as an external machine that needs to be controlled with explicit intentional commands, which in turn leads to severe difficulties in interacting with the world in a fluid and intuitive manner. In consequence, there is a characteristic dissociality: Others become problems to be solved by intellectual effort and no longer present opportunities for spontaneous interpersonal alignment. This dissociality goes (...)
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  26. Knowledge Bases and Neural Network Synthesis.Todd R. Davies - 1991 - In Hozumi Tanaka (ed.), Artificial Intelligence in the Pacific Rim: Proceedings of the Pacific Rim International Conference on Artificial Intelligence. IOS Press. pp. 717-722.
    We describe and try to motivate our project to build systems using both a knowledge based and a neural network approach. These two approaches are used at different stages in the solution of a problem, instead of using knowledge bases exclusively on some problems, and neural nets exclusively on others. The knowledge base (KB) is defined first in a declarative, symbolic language that is easy to use. It is then compiled into an efficient neural network (NN) representation, (...)
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  27. The best game in town: The reemergence of the language-of-thought hypothesis across the cognitive sciences.Jake Quilty-Dunn, Nicolas Porot & Eric Mandelbaum - 2023 - Behavioral and Brain Sciences 46:e261.
    Mental representations remain the central posits of psychology after many decades of scrutiny. However, there is no consensus about the representational format(s) of biological cognition. This paper provides a survey of evidence from computational cognitive psychology, perceptual psychology, developmental psychology, comparative psychology, and social psychology, and concludes that one type of format that routinely crops up is the language-of-thought (LoT). We outline six core properties of LoTs: (i) discrete constituents; (ii) role-filler independence; (iii) predicate–argument structure; (iv) logical operators; (v) inferential (...)
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  28. Subjectivity, nature, existence: Foundational issues for enactive phenomenology.Thomas Netland - 2023 - Dissertation, Norwegian University of Science and Technology
    This thesis explores and discusses foundational issues concerning the relationship between phenomenological philosophy and the enactive approach to cognitive science, with the aim of clarifying, developing, and promoting the project of enactive phenomenology. This project is framed by three general ideas: 1) that the sciences of mind need a phenomenological grounding, 2) that the enactive approach is the currently most promising attempt to provide mind science with such a grounding, and 3) that this attempt involves both a (...)
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  29. Analyzing the Relationship between Smoking and Drinking Patterns Using Neural Networks: A Comprehensive Feature-Based Approach.Ahmed Samir Abu Al-Hussein, Mona Ayman Abu Aisha, Iman Nahed Saeed Ahleel & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (9):18-25.
    This study employs a neural network to analyze the connection between smoking, drinking, and various health-related factors using a dataset of 5148 samples. Achieving an impressive 99.94% accuracy and an average training error of 0.0016, the model identifies influential factors such as serum aminotransferases, serum creatinine, sex, weight, and triglyceride levels. These findings enhance our understanding of lifestyle choices and their impact on health. This research underscores the potential of machine learning in studying complex health phenomena.
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  30. The feeling body: Towards an enactive approach to emotion.Giovanna Colombetti & Evan Thompson - 2008 - In W. F. Overton, U. Mueller & J. Newman (eds.), Body in Mind, Mind in Body: Developmental Perspectives on Embodiment and Consciousness. Erlbaum.
    For many years emotion theory has been characterized by a dichotomy between the head and the body. In the golden years of cognitivism, during the nineteen-sixties and seventies, emotion theory focused on the cognitive antecedents of emotion, the so-called “appraisal processes.” Bodily events were seen largely as byproducts of cognition, and as too unspecific to contribute to the variety of emotion experience. Cognition was conceptualized as an abstract, intellectual, “heady” process separate from bodily events. Although current emotion theory has moved (...)
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  31. Uncovering the antecedents of trust in social commerce: an application of the non-linear artificial neural network approach.Hussam Al Halbusi - 2022 - Competitiveness Review 4.
    Purpose – The internet creates ample opportunities to start a mobile social commerce business. The literature confirms the issue of customer trust for social commerce businesses is a challenge that must be addressed. Hence, this study aims to examine the antecedents of trust in mobile social commerce by applying linear and non-linear relationships based on partial least squares structural equation modeling and an artificial neural network model. -/- Design/methodology/approach – This study applied a non-linear artificial neural network approach (...)
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  32. Improvisation and the self-organization of multiple musical bodies.Ashley E. Walton, Michael J. Richardson, Peter Langland-Hassan & Anthony Chemero - 2015 - Frontiers in Psychology 6:1-9.
    Understanding everyday behavior relies heavily upon understanding our ability to improvise, how we are able to continuously anticipate and adapt in order to coordinate with our environment and others. Here we consider the ability of musicians to improvise, where they must spontaneously coordinate their actions with co-performers in order to produce novel musical expressions. Investigations of this behavior have traditionally focused on describing the organization of cognitive structures. The focus, here, however, is on the ability of the time-evolving patterns of (...)
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  33. 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 (...)
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  34. Certifiable AI.Jobst Landgrebe - 2022 - Applied Sciences 12 (3):1050.
    Implicit stochastic models, including both ‘deep neural networks’ (dNNs) and the more recent unsupervised foundational models, cannot be explained. That is, it cannot be determined how they work, because the interactions of the millions or billions of terms that are contained in their equations cannot be captured in the form of a causal model. Because users of stochastic AI systems would like to understand how they operate in order to be able to use them safely and reliably, there (...)
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  35. Quantum information theoretic approach to the mind–brain problem.Danko D. Georgiev - 2020 - Progress in Biophysics and Molecular Biology 158:16-32.
    The brain is composed of electrically excitable neuronal networks regulated by the activity of voltage-gated ion channels. Further portraying the molecular composition of the brain, however, will not reveal anything remotely reminiscent of a feeling, a sensation or a conscious experience. In classical physics, addressing the mind–brain problem is a formidable task because no physical mechanism is able to explain how the brain generates the unobservable, inner psychological world of conscious experiences and how in turn those conscious experiences steer the (...)
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  36.  57
    Medical Image Classification with Machine Learning Classifier.Destiny Agboro - forthcoming - Journal of Computer Science.
    In contemporary healthcare, medical image categorization is essential for illness prediction, diagnosis, and therapy planning. The emergence of digital imaging technology has led to a significant increase in research into the use of machine learning (ML) techniques for the categorization of images in medical data. We provide a thorough summary of recent developments in this area in this review, using knowledge from the most recent research and cutting-edge methods.We begin by discussing the unique challenges and opportunities associated with medical (...)
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  37. Varieties of representation in evolved and embodied neural networks.Pete Mandik - 2003 - Biology and Philosophy 18 (1):95-130.
    In this paper I discuss one of the key issuesin the philosophy of neuroscience:neurosemantics. The project of neurosemanticsinvolves explaining what it means for states ofneurons and neural systems to haverepresentational contents. Neurosemantics thusinvolves issues of common concern between thephilosophy of neuroscience and philosophy ofmind. I discuss a problem that arises foraccounts of representational content that Icall ``the economy problem'': the problem ofshowing that a candidate theory of mentalrepresentation can bear the work requiredwithin in the causal economy of a mind (...)
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  38. The quantization error in a Self-Organizing Map as a contrast and color specific indicator of single-pixel change in large random patterns.Birgitta Dresp-Langley - 2019 - Neural Networks 120:116-128..
    The quantization error in a fixed-size Self-Organizing Map (SOM) with unsupervised winner-take-all learning has previously been used successfully to detect, in minimal computation time, highly meaningful changes across images in medical time series and in time series of satellite images. Here, the functional properties of the quantization error in SOM are explored further to show that the metric is capable of reliably discriminating between the finest differences in local contrast intensities and contrast signs. While this capability of (...)
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  39. Freedom of the Will and No-Self in Buddhism.Pujarini Das & Vineet Sahu - 2018 - Journal of the Indian Council of Philosophical Research 35 (1):121-138.
    The Buddha, unlike the Upaniṣadic or Brahmanical way, has avoided the concept of the self, and it seems to be left with limited conceptual possibilities for free will and moral responsibility. Now, the question is, if the self is crucial for free will, then how can free will be conceptualized in the Buddhist ‘no-self’ (anattā) doctrine. Nevertheless, the Buddha accepts a dynamic notion of cetanā (intention/volition), and it explicitly implies that he rejects the ultimate or absolute freedom (...)
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  40. A Revolutionary New Metaphysics, Based on Consciousness, and a Call to All Philosophers.Lorna Green - manuscript
    June 2022 A Revolutionary New Metaphysics, Based on Consciousness, and a Call to All Philosophers We are in a unique moment of our history unlike any previous moment ever. Virtually all human economies are based on the destruction of the Earth, and we are now at a place in our history where we can foresee if we continue on as we are, our own extinction. As I write, the planet is in deep trouble, heat, fires, great storms, and record flooding, (...)
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  41. Discourseology of Linguistic Consciousness: Neural Network Modeling of Some Structural and Semantic Relationships.Vitalii Shymko - 2021 - Psycholinguistics 29 (1):193-207.
    Objective. Study of the validity and reliability of the discourse approach for the psycholinguistic understanding of the nature, structure, and features of the linguistic consciousness functioning. -/- Materials & Methods. This paper analyzes artificial neural network models built on the corpus of texts, which were obtained in the process of experimental research of the coronavirus quarantine concept as a new category of linguistic consciousness. The methodology of feedforward artificial neural networks (multilayer perceptron) was used in order to assess (...)
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  42. Climate Change temperature Prediction Using Just Neural Network.Saja Kh Abu Safiah & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (9):35-45.
    Climate change temperature prediction plays a crucial role in effective environmental planning. This study introduces an innovative approach that harnesses the power of Artificial Neural Networks (ANNs) within the Just Neural Network (JustNN) framework to enhance temperature forecasting in the context of climate change. By leveraging historical climate data, our model achieves exceptional accuracy, redefining the landscape of temperature prediction without intricate preprocessing. This model sets a new standard for precise temperature forecasting in the context of climate change. (...)
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  43. Both Materialist & non-Materialist are correct - about themselves: A brain’s self-identification as "Materialist" or “Non-Materialist” (dualist, panpsychist, idealist etc) as reflecting the absence or presence of an associated real non-material awareness/consciousness, rather than merely as a statement of a philosophical stance. A survey will identify relevant candidates of both types for a proposed brain-experiment to determine a possible correlation to the brain’s deep structure/neural wiring.Avi Rabinowitz - manuscript
    We contest the unsubstantiated assumption of both materialists and non-materialist that the ontological status they propose applies to all humans and that the competing claim is false for all - ie we reject both the claim of non-materialists that all humans share the same fundamental aspect of having a "non-material consciousness" (nmc), as well as the contrasting claim of materialists that none do (being fully material as according to eliminative materialists/reductive physicalists etc). Instead, the basic proposition of this paper, our (...)
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  44. PREDICTION OF EDUCATIONAL DATA USING DEEP CONVOLUTIONAL NEURAL NETWORK.K. Vijayalakshmi - 2022 - Journal of Science Technology and Research (JSTAR) 3 (1):93-111.
    : One of the most active study fields in natural language processing, web mining, and text mining is sentiment analysis. Big data is an important research component in education that is used to advance the value of education by watching students' performance and understanding their learning habits. Real-time student feedback will enable teachers and students to understand teaching and learning challenges in the most user-friendly manner for students. By linking learning analytics to grounded theory, the proposed Deep (...)
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  45. Empiricism without Magic: Transformational Abstraction in Deep Convolutional Neural Networks.Cameron Buckner - 2018 - Synthese (12):1-34.
    In artificial intelligence, recent research has demonstrated the remarkable potential of Deep Convolutional Neural Networks (DCNNs), which seem to exceed state-of-the-art performance in new domains weekly, especially on the sorts of very difficult perceptual discrimination tasks that skeptics thought would remain beyond the reach of artificial intelligence. However, it has proven difficult to explain why DCNNs perform so well. In philosophy of mind, empiricists have long suggested that complex cognition is based on information derived from sensory experience, often appealing (...)
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  46. Where there is life there is mind: In support of a strong life-mind continuity thesis.Michael David Kirchhoff & Tom Froese - 2017 - Entropy 19.
    This paper considers questions about continuity and discontinuity between life and mind. It begins by examining such questions from the perspective of the free energy principle (FEP). The FEP is becoming increasingly influential in neuroscience and cognitive science. It says that organisms act to maintain themselves in their expected biological and cognitive states, and that they can do so only by minimizing their free energy given that the long-term average of free energy is entropy. The paper then argues that there (...)
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  47. A Multi-scale View of the Emergent Complexity of Life: A Free-energy Proposal.Casper Hesp, Maxwell Ramstead, Axel Constant, Paul Badcock, Michael David Kirchhoff & Karl Friston - forthcoming - In Michael Price & John Campbell (eds.), Evolution, Development, and Complexity: Multiscale Models in Complex Adaptive Systems.
    We review some of the main implications of the free-energy principle (FEP) for the study of the self-organization of living systems – and how the FEP can help us to understand (and model) biotic self-organization across the many temporal and spatial scales over which life exists. In order to maintain its integrity as a bounded system, any biological system - from single cells to complex organisms and societies - has to limit the disorder or dispersion (i.e., the long-run (...)
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  48. 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 (...)
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  49. Comprehensive Review on Advanced Adversarial Attack and Defense Strategies in Deep Neural Network (8th edition). [REVIEW]Smith Oliver & Brown Anderson - 2023 - International Journal of Research and Innovation in Applied Science:156-166.
    In adversarial machine learning, attackers add carefully crafted perturbations to input, where the perturbations are almost imperceptible to humans, but can cause models to make wrong predictions. In this paper, we did comprehensive review of some of the most recent research, advancement and discoveries on adversarial attack, adversarial sampling generation, the potency or effectiveness of each of the existing attack methods, we also did comprehensive review on some of the most recent research, advancement and discoveries on adversarial defense strategies, (...)
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  50. Making Sense of Raw Input.Richard Evans, Matko Bošnjak, Lars Buesing, Kevin Ellis, David Pfau, Pushmeet Kohli & Marek Sergot - 2021 - Artificial Intelligence 299 (C):103521.
    How should a machine intelligence perform unsupervised structure discovery over streams of sensory input? One approach to this problem is to cast it as an apperception task [1]. Here, the task is to construct an explicit interpretable theory that both explains the sensory sequence and also satisfies a set of unity conditions, designed to ensure that the constituents of the theory are connected in a relational structure. However, the original formulation of the apperception task had one fundamental limitation: it (...)
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