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557 articles for “Neural network”

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Research ArticleOpen accessIn the abstractPost-COVID Impact Analysis and Effective Recommendation Solutions Over Risk Prediction Using Hybrid ModelBoddeti Jaggan Mohan Ravi Kumar, P. V. G. D. Prasad Reddy, G SrinivasThe COVID-19 pandemic (2019-2022) resulted in significant global mortality, largely attributed to the virus's unpredictable pathophysiology, rapid disease progression affecting multiple organ systems, and initial lack of effective treatments. This study systematically examines post-COVID-19 complications across major organ systems, including respiratory dysfunction, cardiovascular complications, renal disorders, musculoskeletal pain, gastrointestinal disturbances, neurological sequelae, alopecia, endocrine and metabolic dysregulation, and mental health … …Journal of Computer Science, Vol. 21, Issue 11 · 23 Dec 2025 · 1,650 accessesView PDFCite
Research ArticleOpen accessIn the abstractRefining Chest X-ray Interpretation with Deep Transfer Learning TechniquesR. Sriramkumar, K. Selvakumar, J. JeganChest X-rays are essential diagnostic tools for thoracic diseases, but different doctors' interpretations can differ greatly, which frequently results in inconsistent diagnoses. By using deep transfer learning techniques, this study seeks to improve the accuracy of Chest X-ray interpretations. More accurate and effective analysis can be accomplished with the growing potential of artificial intelligence (AI) in medical imaging, especially through … …Journal of Computer Science, Vol. 21, Issue 10 · 27 Nov 2025 · 2,655 accessesView PDFCite
Review ArticleOpen accessIn the abstractUnleashing the Power of Image Denoising: A Comprehensive Review of Classical to Deep Learning MethodsArchana Saini, Ayush DograImage denoising is a vital step in many image processing and computer vision professions that aims to improve picture quality by decreasing noise while maintaining important image information. In this article, a detailed overview is presented of traditional and deep learning based picture denoising approaches. Classical methods, such as linear filtering, transform domain techniques, and patch-based approaches like Non-Local Means … …Journal of Computer Science, Vol. 21, Issue 8 · 8 Oct 2025 · 3,114 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmpirical Study on Modified Pre-Trained CNN Architectures for Fitzpatrick17k Skin Diseases Prediction ModellingSteven Matthew, Nur Afny Catur Andryani, Rojali et al.Preventing missed diagnosis of skin diseases is critical for enhancing patient outcomes. Technology support empowered by AI based algorithms have been recently developed to minimize the burden. Convolutional Neural Networks (CNNs) are increasingly utilized for image classification tasks including skin's diseases prediction modelling. Its advancement architectures such as pre-trained models, VGG16 andResNet50 provide a strong foundation to up-skill the prediction … …Journal of Computer Science, Vol. 21, Issue 7 · 8 Jul 2025 · 3,938 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Indoor Asset Tracking: IoT Integration and Machine Learning Approaches for Optimized PerformanceRafiq Hamadamin Maulud, Sadegh Abdollah AminifarIndoor asset tracking entails the surveillance and governance of the position and movement of tangible assets within enclosed spaces, including warehouses, hospitals, and workplaces. Indoor asset tracking systems employ technologies such as Radio Frequency Identification (RFID), Bluetooth Low Energy (BLE), Wi-Fi, and UWB (Ultra-Wideband) to deliver real-time visibility and precise placement of goods. This research introduces indoor asset tracking with … …Journal of Computer Science, Vol. 21, Issue 7 · 7 Jul 2025 · 3,742 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving the Eastern Arabic Hand Written Digits Recognition Using Deep LearningHamdy Morsy, Hashim M. Hasanien et al.Convolutional neural networks CNNs or simply deep learning was designed for the challenging of object recognition such as digits, characters and even objects that can be classified. The deep convolutional networks are designed to be trained through using a large dataset of the classes. The degree of complexity of recognizing handwritten digits are different from person to person and even … …Journal of Computer Science, Vol. 21, Issue 6 · 27 May 2025 · 4,941 accessesView PDFCite
Research ArticleOpen accessIn the abstractA 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 · 5,276 accessesView PDFCite
Research ArticleOpen accessIn the abstractPM-ViT a Framework for the Recognition of Emotions and Proclivity toward Mental Illness Using Facial ExpressionsPriti Rai Jain, Syed Mohammad Khurshaid Quadri, Anuradha KhattarAutomated emotion recognition is being used as a powerful technology in various fields in the present times. Facial Emotion Recognition (FER) aims to identify the emotional states of individuals based on their facial expressions. While in recent years, Convolutional Neural Networks (CNNs) have shown noteworthy performance in image classification tasks, however, the latest adoption of transformers for computer vision tasks … …Journal of Computer Science, Vol. 21, Issue 3 · 27 Jan 2025 · 7,068 accessesView PDFCite
Research ArticleOpen accessIn the abstractFusing CNN Models for Improved Parkinson’s Disease Detection from Handwritten FeaturesSabrina Benredjem, Tahar MekhazniaNeurodegenerative Diseases (NGD) are a group of progressive neurological disorders, including cognitive decline as Alzheimer’s Disease (AD) and Parkinson’s Disease (PD) that result in the progressive loss of neuronal structure or function. This can lead to a variety of symptoms, in this study we are interested in PD one of the neurological diseases that causes the loss of dopamine-producing neurons … …Journal of Computer Science, Vol. 21, Issue 2 · 22 Jan 2025 · 6,313 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Literature Review of Software Defect Prediction Using Deep LearningAhmed Bahaa, Enas Mohamed Fathy, Ahmed Sharaf Eldin et al.The approaches associated with software defect prediction are used to reduce the time and cost of discovering software defects in source code and to improve the software quality in the organizations. There are two approaches to reveal the software defects in the source code. The first approach is concentrated on the traditional features such as lines of code, code complexity, … …Journal of Computer Science, Vol. 17, Issue 5 · 22 May 2021 · 10,973 accessesView PDFCite