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96 results for “Deep Neural Networks”
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Research ArticleOpen accessIn the abstractHematologic Cancer Cell Detection and Classification Using Optimized VGG-19 with Stratified K-fold Cross-ValidationHema Patel, Himal Shah, Gayatri Patel, Atul PatelThe most prevalent pediatric blood malignancy is acute lymphoblastic leukemia (ALL). ALL is a lethal disease in which patients have a lower survival rate. Its prompt detection and precise categorization are essential for successful treatment. Manual microscopic diagnosis is laborious, prone to mistakes, and heavily reliant on specialized knowledge. With stratified 7-fold cross-validation, which assures an equal ratio of normal … …Journal of Computer Science, Vol. 21, Issue 11 · 24 Dec 2025 · 1,822 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
Research ArticleOpen accessIn the abstractAn Intrusion Detection System Using Optimized Deep Learning for IoT NetworksChempavathy B., Mouleeswaran S. K.In the rapidly evolving landscape of Internet of Things (IoT) networks, assuring security is paramount. Cyber-attacks on IoT networks are evolving in complexity and scale. Intruders employ diverse tactics, including malware, Denial of Service (DoS) attacks, along with unauthorized access. This research aims to propose an optimized Deep Learning (DL) based Intrusion Detection System (IDS) to bolster security within IoT … …Journal of Computer Science, Vol. 21, Issue 8 · 9 Oct 2025 · 3,001 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 abstractTowards a Human-Like AGI Architecture: General Intelligence Framework (GIF)Jiran Kurian Puliyanmakkal, Rohini VArtificial Intelligence (AI) has achieved significant breakthroughs but remains limited by its specialization and inability to generalize across domains, unlike human cognition. Current models such as Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) excel at specific tasks but struggle with real-time adaptability and cross-domain generalization. This paper introduces the General Intelligence Framework (GIF), an approach designed to … …Journal of Computer Science, Vol. 21, Issue 7 · 13 Jul 2025 · 4,443 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Vertical Stacking-Based Ensemble Deep Learning Model for Early Diagnosis of Alzheimer's Disease Using Multimodal MRI ScansParvatham Niranjan Kumar, Lakshmana Phaneendra MaguluriEarly detection of Alzheimer's Disease (AD) is crucial for timely interventions that can slow disease progression, enhance quality of life, and assist with future planning. Convolutional Neural Networks (CNNs) are an efficient method for processing image-based data. In this work, we used CNN-based deep learning models to extract structural information from structural MRI (sMRI) and brain neuron connectivity patterns from … …Journal of Computer Science, Vol. 21, Issue 6 · 14 Jun 2025 · 3,106 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Combined Deep Learning Model with Attention Mechanism for Detection of Implant Manufacturer Using X-Ray ImagesAttar Mahay Sheetal, K. SreekumarShoulder replacement surgery is one of the invasive techniques in orthopedic disciplines that replaces dead shoulder joints with prostheses made from polyethylene and metal components. To perform the surgery, there is a need to know the implant accessories and manufacturer of the implant. Some problems arise in a situation where the patient experiences pain and shoulder malfunctions that need replacement, … …Journal of Computer Science, Vol. 21, Issue 6 · 12 Jun 2025 · 3,257 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 abstractClassification of Arabic Comments to Detect Cyberbullying from Social Media Using Convolutional Neural Network and Meta-LearningSarah Mansour Elgaud, Mustafa Ali Abuzaraida, Abdullah AlshehabAs a result of the proliferation of social media, cyberbullying has become widespread in the Arab community on social media and cyberbullying has become a concern targeting individuals and may cause some serious side effects. The problems of Natural Language Processing (NLP) for the Arabic language and its complexity make it difficult to classify texts accurately. In recent years, deep … …Journal of Computer Science, Vol. 21, Issue 3 · 10 Feb 2025 · 6,288 accessesView PDFCite