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141 results for “human detection”

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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 abstractDifferSqueezeNet: A Leaner Defect Detection ModelJose Joao Manrique Franco, Marcelo RudekIn the industrial environment, the inherent limitations of manual inspection have caused the ascent of automated computer vision systems that aim to match or surpass human performance. In this context, the artificial intelligence field has been interested in defect detection with the creation of many machine learning techniques, focusing on Unsupervised and Semi-supervised learning methods. Since most of these methods … …Journal of Computer Science, Vol. 21, Issue 3 · 4 Feb 2025 · 5,727 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Air-Written Real-Time Multilingual Numeral String Recognition System Using Deep Convolutional Neural NetworksMeenal Jabde, Chandrashekhar Himmatrao Patil, Amol D. Vibhute, Shankar MaliAir-writing is a modern practice for free-space writing of characters or words with hand or finger movements. In the new era, hand gestures are commonly used for Human-Computer Interaction (HCI) or controlling machines in several applications. Writing with a finger or holding any object in hand and 3-D movement in the air is helpful for several applications. However, it is … …Journal of Computer Science, Vol. 20, Issue 12 · 8 Nov 2024 · 5,248 accessesView PDFCite
Research ArticleOpen accessIn the abstractCheating Detection in Examinations Using Improved YOLOv8 with Attention MechanismYan Zuo, Soo See Chai, Kok Luong GohExaminations are among the most widely used and effective methods for assessing knowledge mastery, both domestically and internationally, and are extensively used in various talent-selection processes. Currently, offline exam venues usually rely on on-site manual invigilation combined with exam-monitoring videos to further strengthen invigilation efforts. However, this invigilation method not only utilizes large amounts of human and material costs but … …Journal of Computer Science, Vol. 20, Issue 12 · 6 Nov 2024 · 6,253 accessesView PDFCite
Research ArticleOpen accessIn the abstractFacial Recognition and Discovery Using Convolution Deep Learning Neural NetworkAbdel Karim Mohamed BaarehFacial recognition is a critical and well-established topic that has caught the interest of researchers across various application areas. Face detection and identification are critical components of human detection systems. Researchers in different fields used numerous techniques to recognize human faces in various positions considering several features, many results were also obtained. In this research, we aim to use a … …Journal of Computer Science, Vol. 20, Issue 11 · 22 Oct 2024 · 5,243 accessesView PDFCite
Review ArticleOpen accessIn the abstractMachine Learning Integration for Precise Facial Micro-Expression RecognitionViola Bakiasi Shtino, Markela Muça, Senada BushatiThis study advances facial micro-expression recognition through innovative machine-learning techniques, addressing critical needs in psychology, security, and human-computer interaction. The purpose of this study is to improve micro-expression recognition through the optimization of feature transformation and machine learning algorithms. We introduce a novel approach combining Kernel Principal Component Analysis (KPCA) and Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction, … …Journal of Computer Science, Vol. 20, Issue 11 · 22 Oct 2024 · 5,592 accessesView PDFCite
Review ArticleOpen accessIn the abstractHuman Activity Prediction Studies Using Wearable Sensors and Machine LearningDivya Sharma, Usha ChauhanNowadays, Human Activity Recognition (HAR) systems have become so demanding that they find applications in the field of assisted living systems, elderly healthcare systems, smart homes, healthcare monitoring applications, surveillance systems, etc. Due to its increasing demand in computer science; machine learning and deep learning have brought a paradigm shift in the area of sensor-based recognition systems. Providing accurate information … …Journal of Computer Science, Vol. 20, Issue 4 · 14 Feb 2024 · 7,201 accessesView PDFCite
Review ArticleOpen accessIn the abstractAdvances in Forest Fire Detection, Prediction and Behavior: A Comprehensive SurveyAhmad Alkhatib, Khalid JaberForest fires are a major environmental challenge that poses a threat to both human life and ecological health. To effectively prevent and manage forest fires, it is crucial to have reliable detection, prediction and behavior analysis systems in place. This study provides a comprehensive survey of the different approaches and techniques used for forest fire detection, prediction and behavior analysis. … …Journal of Computer Science, Vol. 20, Issue 4 · 7 Feb 2024 · 6,419 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntegrated Monitoring of Endocrine-Disrupting Chemicals: Analytical Chemistry and Biological Assessment ApproachesChangjin Li, Jing Huo, Zijun Dou et al.Endocrine-Disrupting Chemicals (EDCs) in aquatic environments pose significant threats to ecosystems and human health. These compounds interfere with hormonal regulation at low concentrations and have non-monotonic dose-response relationships, posing challenges to conventional risk assessment. This review systematically compares current EDC monitoring methods, including instrumental chemical analysis and receptor-based biological detection systems, to evaluate sensitivity thresholds, sample throughput, and mechanistic selectivity … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 2 · 3 Jul 2026 · 1,081 accessesView PDFCite
Research ArticleOpen accessIn the abstractTomato Leaf Disease Detection by Hybrid Ai and Ml TechnologyP. Loganathan, M. John Britto, Vinston RajaDiseases that affect plants contribute to productivity decline, but they can be managed with ongoing monitoring. It is time-consuming and prone to error to track plant diseases manually. Early disease detection using Artificial Intelligence (AI) and machine vision can lessen negative impacts while also overcoming some of the limitations of continuous human monitoring. Therefore, this study uses both Deep Learning … …Journal of Computer Science, Vol. 21, Issue 12 · 12 Feb 2026 · 1,881 accessesView PDFCite