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292 articles for “Deep Learning (DL)”
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Research ArticleOpen accessEvery word in the titleHybrid Deep Learning for Kidney Stone Detection in CT Scans With Noise Reduction and Feature EnhancementU. M. Fernandes Dimlo, Sreenu Banoth, Priti Bihade et al.The identification of kidney stones using CT scans is an essential but difficult effort in medical diagnostics, frequently obstructed by imaging noise and the complexity of manual interpretation. Although conventional methods are widely used, they suffer from inaccuracies and inefficiencies, necessitating the development of automated diagnostic solutions. This study tackles these issues by presenting HDCNRNet, a hybrid deep learning network … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 2,161 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Intelligent System for Cardiovascular Disease Prediction Using Deep LearningDeepika Arora, Deepak Dudeja, B K AgrawalHeart disease remains among the major causes of death in the world. Hence, accurate and reliable prediction schemes are key. To detect the presence of diseases in early stages, data mining and deep learning algorithms offer powerful tools to determine important trends in large and complex data. To enhance the prediction of cardiac diseases, this paper proposes a hybrid deep … …Journal of Computer Science, Vol. 22, Issue 2 · 9 Mar 2026 · 1,607 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Hybrid Grey Wolf Optimizer and Deep Transfer Learning-Based Intrusion Detection System for IoTKapil Shrivastava, Manish Tiwari, Prasun ChakrabartiThe rapid proliferation of Internet of Things (IoT) devices has driven significant advancements in connectivity and automation, but it has also introduced substantial cybersecurity risks, including intrusions and cyberattacks. To address these challenges, this study proposes a hybrid intrusion detection framework that combines advanced optimization techniques with ensemble deep learning to enhance detection accuracy and computational efficiency. The proposed framework … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 1,506 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Novel Hybrid Machine and Deep Learning Model for Detecting Arabic Phishing EmailsFahad GhabbanPhishing emails are becoming an increasingly popular type of cybercrime on the internet, affecting both businesses and individuals. The attackers generally use various methods to trick victims and extract personal information from them, such as bank details, home addresses, and account information. Many attempts have been proposed to tackle this issue by using filtering mechanisms or automated classification methods which … …Journal of Computer Science, Vol. 22, Issue 1 · 9 Feb 2026 · 1,897 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Novel Deep Learning Approach for Tomato Leaf Disease Detection Using Optimized CNN ArchitectureSunil K. Vithalani, Vipul K. DabhiEarly disease detection in plants is essential for sustaining agricultural yield and guaranteeing food security. A comparative analysis of transformer-based and convolutional based deep learning models for classifying tomato leaf diseases is presented. Specifically, it examines the performance of a Vision Transformer (ViT), tested both in a form of scratch training setup and through transfer learning, against well-known CNN architectures … …Journal of Computer Science, Vol. 22, Issue 1 · 7 Feb 2026 · 3,917 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleWeb Based Multi Feature Propagation Analysis Model for Efficient Disease Interference and Recommendation Using Deep LearningM. Manoj Kumar, R. SivaAccurate prediction of chronic diseases is critical for proactive healthcare management. This paper proposes a Multi-feature Propagation Analysis-based Deep Learning Model (MPADM) to address this challenge. The model integrates diverse patient data, including medical, diagnostic, genetic, and historical features, collected from multiple sources. After preprocessing, the network is trained to calculate distinct Propagation Weights (PWs) for each feature category, Diagnosis … …Journal of Computer Science, Vol. 21, Issue 11 · 29 Jan 2026 · 1,709 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRecognizing Sign Language Gestures Using a Hybrid Spatio-Temporal Deep Learning ModelMeryem Cherrate, My Abdelouahed Sabri, Ali Yahyaouy, Abdellah AarabRecognizing gestures in American Sign Language (ASL) from video data presents significant challenges due to the intricate combination of hand gestures, facial cues, and body motion. In this work, we introduce a hybrid deep learning framework that integrates Convolutional Neural Networks (CNNs) for extracting spatial characteristics with Long Short-Term Memory (LSTM) networks for capturing temporal sequences. The model was trained … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,048 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDeep Learning Synergy: CNNs and Transformers for Epidemic Outbreak ForecastingAlexander R., Shakthi Priya V., Sumathi G. et al.An Accurate prediction of outbreaks is extremely crucial for taking proactive public health interventions, distributing limited resources, and controlling a disease. This paper assesses and also compares the performances of the available deep learning models, namely, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) networks, and Bidirectional Long Short-Term Memory (BiLSTM) networks, in predicting. CNNs are best for feature extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,113 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleBlockchain-Enabled Decisive Red Fox Optimizer-Based Feature Selection With Deep Learning-Based Intrusion Detection SystemC. Ananth, S. Sathiyarani, N. MohananthiniRecently, Intrusion Detection Systems (IDS) using Deep Learning (DL) models become useful in accomplishing network security. The selected features serve as input to the DL model, which is trained on labelled datasets to learn intrinsic patterns distinguishing malicious from normal network behaviour. DL techniques like Convolutional Neural Networks (CNN) are usually utilized. The seamless combination of Public Blockchain (BC) technology … …Journal of Computer Science, Vol. 21, Issue 12 · 20 Jan 2026 · 1,714 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePrivacy-Preserving Deep Federated Learning on the Edge Using Homomorphic Encryption and Secure Multiparty ComputationNoman Aasif Gudur, Mohamed El-Dosuky, Sherif KamelThe increasing volume of consumer data necessitates reliable edge devices for personalized user experiences. Federated Learning (FL) offers a state-of-the-art approach to decentralized machine learning by leveraging data distributed across multiple client devices. However, user data privacy remains vulnerable to corruption through feature heterogeneity and malicious attacks. While several privacy-preserving techniques have been previously implemented, they suffer from implementation constraints … …Journal of Computer Science, Vol. 21, Issue 11 · 21 Dec 2025 · 4,381 accessesView PDFCite