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2,541 results for “CLA”
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Research ArticleOpen accessEvery word in the titleCharacterization of the Earth's Surface State by Unsupervised Classification: Case of Vegetated, Aquatic and Mineral SurfacesJean-Claude Okaingni, Sié Ouattara, Adles Kouassi, Alain ClémentIn this study, we propose an unsupervised classification scheme based on the Dempster-Shafer Theory (TDS) and the Dezert-Smarandache Theory (DSmT) to characterize vegetated, aquatic and mineral surfaces. From pre-processed ASTER satellite images (georeferencing, geometric correction and 15 m re-sampling), neo-channels were produced by determining the spectral indices NDVI, MNDWI and NDBaI, considered as sources of information for classification of a … …American Journal of Applied Sciences, Vol. 15, Issue 7 · 27 Aug 2018 · 8,176 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRation to Produce Milk High in Conjugated Linoleic Acid (CLA) at Smallholder Dairy Farm: An In Vitro ReconstructionDwitami Anzhany, Toto Toharmat, DespalSmallholder dairy farms have shown the best practices for producing milk with high Conjugated Linoleic Acid (CLA). The rations need to be further investigated to explain the digestion process. This study aimed to reconstruct and evaluate the digestion process of five rations that produced milk with high CLA using in vitro method. The rations were collected from five traditional dairy … …American Journal of Animal and Veterinary Sciences, Vol. 17, Issue 2 · 30 May 2022 · 6,616 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleClassification of Normal and Abnormal Lung CT-scan Images Using Cellular Learning AutomataNooshin Hadavi, Md Jan Nordin, Ali Shojaeipour, Mohammad Faidzul NasrudinThis paper proposes a medical pattern recognition system based on the Cellular automata (CA). CA or cellular machine is a dynamic mathematical model that consists of several similar and simple units organized by considerably simple local rules. Each cell acts as a simple computer automaton. This can lead to the implementation of the complex computations through uncomplicated methods. However, the … …Journal of Computer Science, Vol. 16, Issue 1 · 15 Jan 2020 · 7,834 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDual-Branch Shape Texture Learning With Pyramid Residual and Sobel Edge Layers for Rice Variety ClassificationM Pradeep, M SiddappaAutomated rice variety classification categorizes rice types based on features, such as grain texture, shape, color, and size. Traditional handcrafted feature-based models fail at rice classification due to lighting variations, background noise, and environmental conditions, leading to overlapping visual characteristics and frequent misclassification. To address these challenges, this research proposes a novel Dual-Branch Convolutional Neural Network with Pyramid Residual Units … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 627 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAssessing Supervised Classification Algorithms for Mangrove Detection and Differentiation from Other Forest Types in Paiton District, Probolinggo RegencyKaruniawan Puji Wicaksono, Fathor Rohman, Yasushi MitsudaRemote sensing provides an effective approach for monitoring forest cover dynamics, yet distinguishing mangroves from other forest types remains challenging in heterogeneous coastal landscapes. This study compares six supervised classification algorithms: Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Mixture Discriminant Analysis (MDA), Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) for mangrove detection in Paiton, … …OnLine Journal of Biological Sciences, Vol. 26, Issue 3 · 1 Sep 2026 · 844 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEnsemble Feature Selection for Elderly Health Condition ClassificationRattanawadee PanthongFeature selection is a pivotal technique for constructing classification models with high-dimensional data. It facilitates the identification and elimination of redundant or irrelevant features, thereby reducing model complexity and enhancing predictive accuracy. The success of a classification model largely depends on the quality of the selected features. Accordingly, feature selection is performed during data preparation, prior to data processing, to … …Journal of Computer Science, Vol. 22, Issue 8 · 31 Aug 2026 · 774 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleExplainable MedAttn-ResNet50 for Automated Kidney Tumor Classification from CT Images With Grad-CAM VisualizationD. Vetrithangam, Pramod Kumar, Shilpasree S. et al.Kidney tumor classification from CT imaging remains challenging due to CT-specific intensity variations, tumor heterogeneity, and limited clinically meaningful interpretability in existing deep learning models. To address these limitations, we propose an Explainable MedAttn-ResNet50 framework that integrates radiology-driven preprocessing, multi-scale feature extraction, and medical attention mechanisms within a unified architecture. The preprocessing pipeline applies radiology-inspired intensity normalization, contrast enhancement, and … …Journal of Computer Science, Vol. 22, Issue 8 · 13 Aug 2026 · 1,120 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEW-GAT: Edge-Weighted Graph Attention Framework for Patient-Aware Heart Disease Classification Using Feature-to-Feature Similarity GraphsRamakrishna Reddy Badveli, Nijaguna Gollara Siddappa, Sundeep Kumar KanipakapatnamHeart disease remains an important cause of global death, requiring accurate and clinically interpretable prediction models. However, traditional Machine Learning (ML) methods often fail to capture meaningful dependencies among clinical features and lack robustness across diverse patient populations. To overcome these issues, this research introduces an Edge-Weighted Graph Attention Network (EW-GAT) for patient-aware heart disease classification. The approach first models … …Journal of Computer Science, Vol. 22, Issue 7 · 25 Jul 2026 · 912 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAnimal Health Prediction Using Hybrid CNN Based BiLSTM Classification Model: A Deep Learning ApproachJ. Rathi, A. SumathiAccurate prediction of animal diseases is vital in veterinary medicine, as it can substantially enhance animal health outcomes and mitigate economic losses, making it a critical task that warrants attention and innovative solutions. This paper proposes a novel approach to animal condition classification, leveraging an Auto-encoder-based feature selection process and an Improved Hybrid Convolutional Neural Networks (CNN) with Bidirectional (Bi-LSTM) … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,481 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOptimized Vehicle Insurance Claim and Settlement Procedures Using IOT Sensors on a Blockchain-Based PlatformPreeti Sharma, Meenakshi Malik, Chander Prabha et al.The conventional vehicle insurance claim and settlement landscape is characterised by significant inefficiencies, including cumbersome claim submissions, arbitrary damage assessments, and susceptibility to fraudulent activities. These problems lead to a longer processing time, higher operational cost to the insurers and a reduction in policyholder satisfaction. To address these important challenges, this study proposes a streamlined vehicle insurance claims system that … …Journal of Computer Science, Vol. 22, Issue 3 · 26 Mar 2026 · 1,628 accessesView PDFCite