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141 results for “human detection”
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Research ArticleOpen accessIn the abstractLiDAR-Based Obstacle Detection and Avoidance for Navigation and Control of an Unmanned Ground Robot Using Model Predictive ControlSai Charan Dekkata, Sun Yi, M. A. Muktadir, Selorm GarfoUnmanned Ground Vehicles (UGVs) have, as of late, been utilized in a wide assortment of utilizations because of their flexibility, diminished expense, and quick response, among other benefits. Search and Rescue (SAR) is quite possibly the most conspicuous zones for the work of UGVs instead of a monitored mission, mainly due to its impediments on the expenses, human resources, and … …Journal of Mechatronics and Robotics, Vol. 7, Issue 1 · 30 Mar 2023 · 8,219 accessesView PDFCite
Research ArticleOpen accessIn the abstractGender Classification from Face and Eyes Images Using Deep Learning AlgorithmZahraa Salam Abu Ghrban, Nidhal Khdhair EL AbbadiGender classification provides additional information about the individual’s identity, which is crucial in surveillance, smart interface, and smart advertising, it is a very important aspect of face analysis that has piqued the interest of researchers in areas such as demographic information collection, surveillance, human-computer interaction, marketing intelligence, security, etc. Usually, facial images are used to extract features for classification. This … …Journal of Computer Science, Vol. 19, Issue 3 · 24 Feb 2023 · 6,946 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 · 1,089 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 · 1,889 accessesView PDFCite
Research ArticleOpen accessIn the abstractConvergence of GenAI and RPA: A Digital Heaven in Supply Chain Optimization ProcessSaurabh A. Pahune, Zahid Akhtar, Manoj Chandrasekharan et al.One of the most groundbreaking advances in the field of intelligent automation is the merging of Generative Artificial Intelligence (GenAI) and Robotic Process Automation (RPA). This combination unlocks previously unachievable capabilities in automation. RPA (software bots) improves speed and operational efficiency by automating rule-based tasks, Standard Operating Procedures (SOPs), and repetitive workflows. At the same time, it minimizes manual labor … …Journal of Computer Science, Vol. 21, Issue 12 · 8 Feb 2026 · 2,049 accessesView PDFCite
Review ArticleOpen accessIn the abstractAI-Driven Innovations in Meat Quality and Safety: Applications, Challenges, and Future DirectionsEmrobowansan Monday IdamokoroArtificial Intelligence (AI) is revolutionizing the meat sector by improving efficiency, accurateness, as well as sustainability in meat production, quality evaluation, and safety control. The conventional systems of meat inspection, handling, and processing are usually time consuming, labour-intensive, prone to contamination during handling and often susceptible to human errors. The use of artificial intelligence to drive technologies, including Deep Learning … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 3 · 28 Jan 2026 · 3,686 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Pipelines for Intelligent Human Resources Text Classification: LLMs, RAG, and Generative AISoumia Chafi, Mustapha Kabil, Abdessamad KamoussThe digital transformation of Human Resources Information Systems (HRIS) requires advanced approaches to process unstructured textual data originating from Curriculum Vitae (CVs), cover letters, and job postings. Traditional text classification methods exhibit limitations when faced with current needs for contextual understanding and fine-grained skill detection. This paper proposes a hybrid pipeline combining advanced text classification, contrastive learning (SimCSE, Contriever), Retrieval-Augmented … …Journal of Computer Science, Vol. 22, Issue 4 · 22 Apr 2026 · 1,513 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Approach for Differentiating AI-Generated and Real Images Using Gabor and Color Layout Filters (GF and CLF)G. Ayyappan, A. Thankaraj, S. Surendran et al.The emergence of generative AI images has profoundly upended the art world. Distinguishing AI-generated images from human-created artwork is increasingly challenging. If this issue remains unresolved, dishonest individuals may exploit those who are willing to pay more for original artwork and businesses whose stated policies exclude AI graphics. There are a number of methods for differentiating AI photos from human … …Journal of Computer Science, Vol. 22, Issue 2 · 3 Mar 2026 · 1,756 accessesView PDFCite
Research ArticleOpen accessIn the abstractDefect Detection on 3D Print Products and in Concrete Structures Using Image Processing and Convolution Neural NetworkSelorm Garfo, M.A. Muktadir, Sun YiThis paper explores the automated detection of surface defects on 3-D printed products and concrete structures. They are the main factors to evaluate their quality in addition to dimension and roughness. Traditional detection by human inspectors is far from satisfactory. Manual inspection is time-consuming, error-prone and often leads to loss of resources. For this purpose, image processing and deep learning-based … …Journal of Mechatronics and Robotics, Vol. 4, Issue 1 · 26 May 2020 · 12,619 accessesView PDFCite