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141 results for “human detection”
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Research ArticleOpen accessIn the keywordsSecurity Guard Robot Detecting Human Using Gaussian Distribution Histogram MethodMbaitiga ZacharieProblem statement: The purpose of any robotic is to perform tasks that a human would prefer not to do or hopefully do it with precision in order to avoid mistakes or when a human is out of duty due to fatigue or health reasons. The research into human detection into images has paid the way be aware of what is … …Journal of Computer Science, Vol. 6, Issue 10 · 5 Aug 2010 · 7,059 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHigh-precision Detection of Facial Landmarks to Estimate Head Motions Based on Vision ModelsXiaohong W. Gao, Sergey Anishenko, Dmitry Shaposhnikov et al.A new approach of determination of head movement is presented from the pictures recorded via digital cameras monitoring the scanning processing of PET. Two human vision models of CIECAMs and BMV are applied to segment the face region via skin colour and to detect local facial landmarks respectively. The developed algorithms are evaluated on the pictures (n=12) monitoring a subject’s … …Journal of Computer Science, Vol. 3, Issue 7 · 31 Jul 2007 · 6,820 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Kidney Stone Detection Accuracy Using Image Processing and a Hybrid Convolutional Deep Belief NetworkGeetha M. N, Barkathulla A, S. Nandhini Devi et al.Automated CKD is a rapidly expanding non-communicable ailment that significantly contributes to global mortality and morbidity. CKD impacts more than 10% of the worldwide population, leading to millions of deaths annually. This paper proposes an enhanced deep learning model for renal disease detection that integrates convolutional and involution layers to enhance classification accuracy. CKD is a worldwide health issue characterised … …Journal of Computer Science, Vol. 22, Issue 10 · 9 Oct 2026 · 774 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Optimized YOLOv11-Based Deep Learning Framework With CNN Feature Enhancement for Tile Crack DetectionVinod Kumar Pal, Pankaj MudholkarThe tile business is a critical part of the national economic development, as it is one of the areas that provides employment, produces goods, and exports them. Regardless of its significance, there are challenges in the industry that are caused by issues with production, which in most cases is caused by low-quality materials used or by mishandling of the products … …Journal of Computer Science, Vol. 22, Issue 8 · 12 Aug 2026 · 990 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Sentiment Analysis Approach for Affective State Recognition With SWISH-Activated DenseNet-169 in Human Event ForecastingKarthik Elangovan, Prabhakaran Paulraj, Dinesh Babu G L et al.Detecting human feelings from images is perhaps one of the most useful and challenging social communication problems in research. Emotion detection-based deep computing outperforms classic image processing techniques. Facial recognition technology has permeated every aspect of our daily lives, from unlocking our phones to getting private file access on our systems. Machine Learning and Deep Learning make it easy to … …Journal of Computer Science, Vol. 22, Issue 8 · 29 Jul 2026 · 1,220 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning and Image Analytics for Forest Land Management: Classification, and Object DetectionDevam Dixit, Aditya Bhavsar, Shreyas Jani, Nilesh YadavRapid urbanization and industrialization have contributed to deforestation which has led to a severe degradation of the environment and biodiversity loss. Traditional field survey methods are not applicable in the monitoring of large forest areas due to the fact that such methods are manual, costly and time consuming as well as subject to human error. The current methods of remote … …Journal of Computer Science, Vol. 22, Issue 3 · 26 Mar 2026 · 1,602 accessesView PDFCite
Research ArticleOpen accessIn the abstractTowards an Explainable Approach: Hybrid Residual Network and SVM for Automated Brain Tumor Detection and ClassificationKamini Lamba, Shalli RaniThe abnormal growth of brain cells leads to tumor formation, which can be fatal if not detected and treated promptly. Given the complexity of brain tumors, early detection is critical in healthcare. Traditional radiology-based tumor detection is prone to human error and delays. Hence, a computer- assisted method is needed for accurate and efficient diagnosis. With the rapid advancements in … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,435 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Study of Machine Learning Algorithms for Skin Cancer DetectionVineeth Victor, Amit Kumr Tyagi, Khushboo Tripathi et al.The skin is the largest organ in the human body, covering an area of around 20 square feet. Our skin keeps us safe from germs and the environment, helps us regulate our body temperature, and gives us the ability to feel touch, heat, and cold. More than 95 percent of all skin cancers are caused by ultraviolet (UV) radiation. UV … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 1,869 accessesView PDFCite
Research ArticleOpen accessIn the abstractInternet of Things and Human Neocortex Inspired Algorithms for the Plant Disease Prediction-Sheath Blight for Paddy PlantThangaraj Ethilu, K. Parthiban, Arockia Jayadhas S et al.Sheath blight disease (Rhizoctonia solani) poses a critical threat to paddy (Oryza sativa) production, causing up to 50% yield losses under conducive environmental conditions. Existing computer vision-based disease detection systems identify infections only after symptom manifestation, while conventional machine learning prediction models suffer from high computational demands, data preprocessing requirements, and noise sensitivity. This research proposes a novel Hierarchical Temporal … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 1,780 accessesView PDFCite
Research ArticleOpen accessIn the abstractAssessing Bi-LSTM Model’s Performance in Identifying AI Generated Text in Digital MediaTinashe Crispen Garidzira, William Tichaona Vambe, Courage MatoboboThe rapid growth of AI-generated content from ChatGPT, Gemini, and many others poses significant challenges in digital media. There are increasing instances of text generated by machine learning models being indistinguishable from human-written text. This calls for an effective way of detecting and distinguishing text generated by AI from human text. Using a Cross-Industry Standard Process for Data Mining (CRISP-DM) … …Journal of Computer Science, Vol. 21, Issue 8 · 8 Oct 2025 · 2,424 accessesView PDFCite