This article aims to enhance understanding of the changing nature of the pre-colonial, (neo)colonial and postcolonial imagination of space and time in Africa and of its organising principle in African cinema. It will focus on the cartographic and time reckoning techniques and traditions of Africans in precolonial times in contrast to the space-time imagination expressed in colonial film in Africa, such as in the instruction documentary Daybreak in Udi (1949). This documentary, which promotes British colonial self-help development projects in Africa, (...) tells the story of the building of a maternity home in an Igbo village in Nigeria. Furthermore, the article will enhance understanding of the cinematic turn to a counterhegemonic film tradition as a stepping stone to the newly emerging field of African intercultural philosophical cinema. The time-space imagination in Common Threads (2018), shortlisted by the Zanzibar International Film Festival (ZIFF) for the best documentary will be analysed as a case in point. This documentary concentrates on the nineteenth-century and current Afro-Indian textile trade, the associated oral narratives and their visual impact on the so-called Kanga and Vitenge textiles. (shrink)

Traffic sign detection and recognition (TSDR) is a critical aspect of autonomous driving and intelligent transportation systems. Traditional methods of traffic sign detection rely on handcrafted features and classical machine learning algorithms, which often struggle to achieve high accuracy in complex real-world environments. In contrast, deep learning techniques, particularly Convolutional Neural Networks (CNNs), have shown remarkable performance in both detecting and recognizing traffic signs in diverse conditions. This paper reviews the application of deep learning methods for TSDR, focusing on recent (...) advancements in the use of CNNs, Region-based CNNs (R-CNNs), and YOLO (You Only Look Once) for real-time detection and recognition of traffic signs. We discuss the challenges, including the variability of traffic signs, environmental factors, and computational requirements, and present solutions proposed in the literature. The paper also highlights future directions for improving the robustness, accuracy, and speed of traffic sign detection and recognition systems, with an emphasis on real-time applications. (shrink)

Traffic sign detection and recognition (TSDR) is a critical aspect of autonomous driving and intelligent transportation systems. Traditional methods of traffic sign detection rely on handcrafted features and classical machine learning algorithms, which often struggle to achieve high accuracy in complex real-world environments. In contrast, deep learning techniques, particularly Convolutional Neural Networks (CNNs), have shown remarkable performance in both detecting and recognizing traffic signs in diverse conditions. This paper reviews the application of deep learning methods for TSDR, focusing on recent (...) advancements in the use of CNNs, Region-based CNNs (R-CNNs), and YOLO (You Only Look Once) for real-time detection and recognition of traffic signs. We discuss the challenges, including the variability of traffic signs, environmental factors, and computational requirements, and present solutions proposed in the literature. The paper also highlights future directions for improving the robustness, accuracy, and speed of traffic sign detection and recognition systems, with an emphasis on real-time applications. (shrink)

The early detection of plant diseases is essential to preventing crop losses in terms of quantity and productivity. Farmers typically identify illnesses using their prior knowledge or by spending a great deal of time, effort, and experience doing so. Exceedingly challenging to manually monitor plant diseases. In the development of automatic pathogens diagnosis machines, paddy disease detection is crucial . To identify previously known bacterial leaf blight, brown spot, leaf blast, leaf smut, and other narrow illnesses in prior knowledge, we (...) presented a VGG 16 model in this work. Images of various categories diseases are stored in a special data repository, with 80 percent of the data used for training and 20 percent for sample testing. ResNet, Inception v2 and Mobile Net were all used in the model-building process to add benefits. The results of the interpretation show that there is high level picture classification accuracy and low mistake rate. As a result, our model excels at identifying paddy diseases and may be used in practical applications in daily life. (shrink)

This twelfth volume of Collected Papers includes 86 papers comprising 976 pages on Neutrosophics Theory and Applications, published between 2013-2021 in the international journal and book series “Neutrosophic Sets and Systems” by the author alone or in collaboration with the following 112 co-authors (alphabetically ordered) from 21 countries: Abdel Nasser H. Zaied, Muhammad Akram, Bobin Albert, S. A. Alblowi, S. Anitha, Guennoun Asmae, Assia Bakali, Ayman M. Manie, Abdul Sami Awan, Azeddine Elhassouny, Erick González-Caballero, D. Dafik, Mithun Datta, Arindam Dey, (...) Mamouni Dhar, Christopher Dyer, Nur Ain Ebas, Mohamed Eisa, Ahmed K. Essa, Faruk Karaaslan, João Alcione Sganderla Figueiredo, Jorge Fernando Goyes García, N. Ramila Gandhi, Sudipta Gayen, Gustavo Alvarez Gómez, Sharon Dinarza Álvarez Gómez, Haitham A. El-Ghareeb, Hamiden Abd El-Wahed Khalifa, Masooma Raza Hashmi, Ibrahim M. Hezam, German Acurio Hidalgo, Le Hoang Son, R. Jahir Hussain, S. Satham Hussain, Ali Hussein Mahmood Al-Obaidi, Hays Hatem Imran, Nabeela Ishfaq, Saeid Jafari, R. Jansi, V. Jeyanthi, M. Jeyaraman, Sripati Jha, Jun Ye, W.B. Vasantha Kandasamy, Abdullah Kargın, J. Kavikumar, Kawther Fawzi Hamza Alhasan, Huda E. Khalid, Neha Andalleb Khalid, Mohsin Khalid, Madad Khan, D. Koley, Valeri Kroumov, Manoranjan Kumar Singh, Pavan Kumar, Prem Kumar Singh, Ranjan Kumar, Malayalan Lathamaheswari, A.N. Mangayarkkarasi, Carlos Rosero Martínez, Marvelio Alfaro Matos, Mai Mohamed, Nivetha Martin, Mohamed Abdel-Basset, Mohamed Talea, K. Mohana, Muhammad Irfan Ahamad, Rana Muhammad Zulqarnain, Muhammad Riaz, Muhammad Saeed, Muhammad Saqlain, Muhammad Shabir, Muhammad Zeeshan, Anjan Mukherjee, Mumtaz Ali, Deivanayagampillai Nagarajan, Iqra Nawaz, Munazza Naz, Roan Thi Ngan, Necati Olgun, Rodolfo González Ortega, P. Pandiammal, I. Pradeepa, R. Princy, Marcos David Oviedo Rodríguez, Jesús Estupiñán Ricardo, A. Rohini, Sabu Sebastian, Abhijit Saha, Mehmet Șahin, Said Broumi, Saima Anis, A.A. Salama, Ganeshsree Selvachandran, Seyed Ahmad Edalatpanah, Sajana Shaik, Soufiane Idbrahim, S. Sowndrarajan, Mohamed Talea, Ruipu Tan, Chalapathi Tekuri, Selçuk Topal, S. P. Tiwari, Vakkas Uluçay, Maikel Leyva Vázquez, Chinnadurai Veerappan, M. Venkatachalam, Luige Vlădăreanu, Ştefan Vlăduţescu, Young Bae Jun, Wadei F. Al-Omeri, Xiao Long Xin.‬‬‬‬‬‬. (shrink)