Research ArticleOpen accessEvery word in the titleImage-Based Alzheimer's Disease Detection Using Pretrained Convolutional Neural Network ModelsNasser AlsadhanAlzheimer's disease is an untreatable, progressive brain disorder that slowly robs people of their memory, thinking abilities, and ultimately their capacity to complete even the most basic tasks. Among older adults, it is the most frequent cause of dementia. Although there is presently no treatment for Alzheimer's disease, scientific trials are ongoing to discover drugs to combat the condition. Treatments … …Journal of Computer Science, Vol. 19, Issue 7 · 28 Jun 2023 · 5,909 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPHASEY: A Contrastive Learning Approach for Enhanced Human Gait Phases RecognitionUrvashi, Deepak Kumar, Vinay Kukreja, Ayush DograHuman gait has gained much attention in behavioral biometrics as it possesses unique and distinctive characteristics. Gait phases, which describe the different patterns of human walking, are significant for the analysis and understanding of movement in an individual. Hence, the identification of gait phases is important for the accurate determination and interpretation of walking patterns, ranging from healthcare and security … …Journal of Computer Science, Vol. 21, Issue 8 · 16 Sep 2025 · 4,638 accessesView PDFCite
Research ArticleOpen accessIn the abstractRemote Sensing Image Classification Using Convolutional Neural Network (CNN) and Transfer Learning TechniquesMustafa Majeed Abd Zaid, Ahmed Abed Mohammed, Putra SumariThis study investigates the classification of aerial images depicting transmission towers, forests, farmland, and mountains. To complete the classification job, features are extracted from input photos using a Convolutional Neural Network (CNN) architecture. Then, the images are classified using Softmax. To test the model, we ran it for ten epochs using a batch size of 90, the Adam optimizer, and … …Journal of Computer Science, Vol. 21, Issue 3 · 11 Feb 2025 · 10,117 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Approaches for Brain Tumor Diagnosis using Fused Layer AcceleratorMitrabinda Khuntia, Prabhat Kumar Sahu, Swagatika DeviDeep Convolutional Neural Networks (DCNNs) are an emerging field in biomedical processing. Tumor classification is a key stage in the pathology analysis process, and deep learning algorithms for brain tumor categorization have recently shown promising results. However, these approaches often require more storage and more expensive training procedures to input a large number of training variables. To address this issue, … …Journal of Computer Science, Vol. 19, Issue 2 · 19 Jan 2023 · 5,787 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Conceptual Framework for Efficient and Sustainable Pruning Techniques in Deep Learning ModelsNyalalani Smarts, Rajalakshm Selvaraj, Venumadhav KuthadiThis research paper proposes a conceptual framework and optimization algorithm for pruning techniques in deep learning models, its focus is on key challenges such as model size, computational efficiency, inference speed and sustainable technology development. The aim of the framework is to transition from large neural networks to sparse, efficient models, indicating the benefits of pruning in improving model scalability … …Journal of Computer Science, Vol. 21, Issue 5 · 26 Apr 2025 · 5,268 accessesView PDFCite