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179 results for “Multi-Class”
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Research ArticleOpen accessIn the abstractSystematic Literature Review of Graph Neural Networks in Disaster Management: Methods, Applications, and Future DirectionsSularno, Wendi Boy, Putri Anggraini et al.The increasing frequency and complexity of natural disasters underscore the urgent need for intelligent systems that support timely and effective decision-making. Graph Neural Networks (GNNs) have emerged as a powerful deep-learning paradigm for modeling spatial and relational data, offering distinct advantages for disaster management. This study presents a Systematic Literature Review (SLR) of GNN-based approaches for disaster mitigation, emergency response, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,043 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Dam Safety and Management: Long Short-Term Memory Based Predictive Models for Accurate Alert ForecastingNisha C. M, N. ThangarasuDam management and early alert systems are critical for effective water resource management. Accurate prediction of dam alert signals facilitates proactive decision-making, thereby aiding in the effective management and reduction of potential risks linked to dam operations. Within this research, Long Short-Term Memory (LSTM) networks are utilized to forecast dam alert signals issued from the dam by leveraging daily parameters, … …Journal of Computer Science, Vol. 22, Issue 1 · 6 Feb 2026 · 1,632 accessesView PDFCite
Research ArticleOpen accessIn the abstractWeb 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 · 1,715 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving the Detection of Mask-Wearing Mistakes by Deep LearningChahinez Mérièm BentaouzaThis study focuses on the detection of wearing mask errors after machine learning by a Multi-Layer Perceptron Mixer (MLP Mixer) applied to protect masks from COVID-19. To combat the spread of the COVID-19 pandemic, facemasks have become an essential accessory, so it's necessary to identify individuals who follow this health protection. In this case, the most successful face-detection method Viola-Jones … …Journal of Computer Science, Vol. 20, Issue 7 · 25 Apr 2024 · 5,198 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Vision System Based on Time-of-Flight and RGB Cameras Applied to Robotic Tree Peony Fruit HarvestingJiaming Liu, Dong Zhao, Tianxing Li, Jian ZhaoTree peony is a deciduous shrub endemic to China and the Peony Seed Oil (PSO) is an important plant oil resource. However, at present, fruits harvesting of peony are mainly completed by manual work with low efficiency. In response to the need for a mechanized operation, a multi-sources vision system based on Time-Of-Flight (TOF) and RGB cameras was set up … …American Journal of Biochemistry and Biotechnology, Vol. 16, Issue 3 · 19 Aug 2020 · 6,332 accessesView PDFCite
Research ArticleOpen accessIn the abstractEstimation and Reliability for a Special Type of Semi-Markov ProcessVlad Stefan Barbu, Alex Karagrigoriou, Andreas MakridesThis work deals with multi-state systems modelled by means of semi-Markov processes. The sojourn times are seen to be independent not identically distributed random variables and assumed to belong to one of two different general classes of distributions so that the first class is closed under maxima and the second one is closed under minima. We obtain maximum likelihood estimators … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 20 Oct 2019 · 7,049 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluating Barriers to the Adoption of Augmented Reality-based Applications in Education System: DEMATEL ApproachMonika Nijhawan, Nidhi Sindhwani, Sarvesh Tanwar, Shishir KumarAugmented Reality (AR) is an emerging technology that enhances user perception by overlaying virtual information onto the physical world. In educational contexts, AR integration has demonstrated potential to improve learning engagement, motivation, and conceptual understanding among students. However, teachers face numerous challenges when incorporating AR technologies into classroom instruction, including technical difficulties stemming from inadequate training, resistance to technology adoption, … …Journal of Computer Science, Vol. 21, Issue 10 · 17 Dec 2025 · 2,422 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Multi-Layer Perceptron and Enhanced Edge-Free Active Contour Model Lung Nodule Detection AlgorithmShengguang PengA computer-assisted method is usually used to identify pneumoconiosis by segmenting and classifying the initial area of interest. The accuracy of current techniques for segmenting and classifying lung nodules is often suboptimal. Therefore, a hybrid Multi-Layer Perceptron (MLP) and enhanced edge-free active contour model (CV) algorithm are proposed to solve this problem. First, lung nodules are identified by the MLP … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 1 · 25 Jan 2025 · 5,550 accessesView PDFCite
Research ArticleOpen accessIn the abstractPedestrian Recognition Based on Multi-Scale Weighted HOGMonther Hussein Al-BsoolPedestrian recognition receives a great attention in recent years due to its importance in traffic accidents identification. Traffic surveillance systems can provide valuable information for pedestrian recognition using computer vision and image processing techniques. Most techniques exploit simple feature extraction and multi-stage feature matching to train classifiers. In this study, Canny edge information and Histogram of Oriented Gradient (HOG) has … …Journal of Computer Science, Vol. 14, Issue 11 · 7 Nov 2018 · 7,161 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassifications of Skull Fractures using CT Scan Images via CNN with Lazy Learning ApproachMd Moniruzzaman Emon, Tareque Rahman Ornob, Moqsadur RahmanClassification of skull fracture is a challenging task for both radiologists and researchers. Skull fractures result in broken pieces of bone, which can cut into the brain and cause bleeding and other injury types. So it is vital to detect and classify the fracture very early. In real world, often fractures occur at multiple sites. This makes it harder to … …Journal of Computer Science, Vol. 18, Issue 3 · 15 Mar 2022 · 9,012 accessesView PDFCite