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170 articles for “recognition accuracy”
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Research ArticleOpen accessIn the abstractEdge Computing Enabled Human Activity Recognition (ECEHAR) Using LSTM and CNNSuresh Kumar, M Y. Mohamed ParveesHuman Activity Recognition (HAR) is an important research area for various application domains such as healthcare, gaming, telemonitoring, and sports. However, executing HAR algorithms on remote servers or in the cloud have challenges in terms of high latency, increased bandwidth demand, and high energy consumption. Moving the computation to edge-assisted HAR is more effective and flexible solution to address the … …Journal of Computer Science, Vol. 22, Issue 3 · 6 Mar 2026 · 1,578 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized WFST-Based ASR for Arabic: Balancing Memory, Speed, and AccuracyWael A. Sultan, Mourad S. Semary, Sherif M. AbdouWeighted Finite-State Transducers (WFSTs) have revolutionized Automatic Speech Recognition (ASR) by enabling significantly faster decoding speeds compared to traditional systems that build the search space progressively. However, applying WFSTs to morphology-rich languages such as Arabic presents challenges due to the large vocabulary, resulting in extensive networks that exceed the memory capacity of standard CPUs. This study introduces various strategies to … …Journal of Computer Science, Vol. 22, Issue 2 · 23 Feb 2026 · 1,442 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Multi Task Analysis Model Based on EEG Features in the Study of the Correlation between Depression and Sleep Disorders in College StudentsFeng MaWith the improvement of multi-modal technology, research on depression recognition combining multiple biological signal features has been increasing. Electroencephalogram signals reflect brain activity, and by analyzing their characteristics, the accuracy and stability of depression recognition can be effectively improved. Therefore, this study proposes a correlation analysis between depression and sleep disorders in college students based on electroencephalogram feature analysis, innovatively … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 4 · 2 Feb 2026 · 1,994 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Occlusion Aware Facial Expression Recognition Model Using Fitness Based Cheetah Optimizer and Adaptive Multi-Scale ViT-CNN With Attention MechanismA. Reddy Prasad, A. RajeshAs a highly nuanced aspect of human communication, facial expression recognition presents a computationally complex problem, making it a prominent area of research in computer vision and affective computing. Problems like poor image quality, occlusions, inconsistent illumination, and head attitude changes are frequently observed in images taken from unstructured sources such as the internet that affect the accuracy of facial … …Journal of Computer Science, Vol. 21, Issue 12 · 29 Jan 2026 · 1,962 accessesView PDFCite
Research ArticleOpen accessIn the abstractRecognizing 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 accessIn the abstractBlockchain-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 accessIn the abstractEnhancing E-Banking Security and Personalization through Convolutional Neural Network-Based Facial RecognitionRamy Kamal Amin, Ghada A. El Khayat, Farid El Sahn, Abeer A. AmerFacial recognition technology has become a cornerstone in enhancing the security and user experience of electronic banking services. Its ability to provide a seamless yet secure authentication method is vital in combating fraud and maintaining the integrity of online financial transactions. This study presents the development of an advanced electronic banking system that strengthens security through the integration of a … …Journal of Computer Science, Vol. 21, Issue 10 · 7 Dec 2025 · 3,310 accessesView PDFCite
Research ArticleOpen accessIn the abstractDistributed Vehicle Tracking System Using Image Processing TechniquesIehab Abdul Jabbar Kamil, Mohanad Abdulsalam Al-AskariIn this part of the research, an implementation of a distributed vehicle tracking system that uses image processing techniques for real-time automobile surveillance is done. The system uses OpenCV, Pytesseract and Optical Character Recognition (OCR) for the extraction of the license plate information from vehicle images to identify and track vehicles. By doing so, distributed computing enables the system to … …Journal of Computer Science, Vol. 21, Issue 8 · 9 Oct 2025 · 2,263 accessesView PDFCite
Research ArticleOpen accessIn the abstractPHASEY: 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 abstractAnnotation of Facial Expressions (Navarasa) in Videos Using Deep LearningReshma M R, Kannan B, Jagathy Raj V P, Shailesh SFacial expression plays a significant role in understanding human behavior, alongside other relevant elements such as body posture, gait, and hand gestures. In the context of Indian Classical Dance (ICD), these elements work together to convey the stories depicted by characters from Indian mythology. Accompanying songs and shlokas evoke emotions, reflected in performers' facial expressions known as the performance. In … …Journal of Computer Science, Vol. 21, Issue 6 · 14 Jun 2025 · 4,093 accessesView PDFCite