250 results for “neural network approach”

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Research ArticleOpen accessEvery word in the titleIdentification of Influential Nodes With Topological Structure Via GRAPH Neural Network (GNN) Approach in Social Media NetworksRajnish Kumar, Laxmi Ahuja, Suman Mann, Sanmukh KaurThe amount of data in social networks is vast these days, and constantly changing, making influential node identification crucial. The existing topologies are constantly changing due to the evolving behavior of the applied dataset. Node and leaf topology or feature-based value form the basis for machine learning and centrality computation. Hence, influential node value determination is based on the node … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 1,830 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleApplying Neural Network-Based Approach to Sickle Cell Disease-Related Pain ClassificationZacchaeus Omogbadegun, Israel Ogundele, Olufunke OladipupoSickle Cell Disease (SCD), an inherited Red Blood Cell (RBC) disorder, is characterized by anaemia, end-organ damage, unpredictable episodes of pain and early mortality. SCD affects 25% of people living in Central and West Africa causing life threatening “silent” strokes and lifelong damage. Nigeria accounts for 50% of SCD births worldwide (estimated 150,000 of 300,000 babies born with Symptomatic Sickle … …Journal of Computer Science, Vol. 15, Issue 6 · 28 Jun 2019 · 7,678 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleThe Artificial Neural Network Based Approach for Mortality Structure AnalysisSokolova M. Kursk, Rashad J. Rasras, D. SkopinThe theoretical outcomes and experimental results of applying of Artificial Neural Networks towards mortality structure examination in Russian Federation are presented in the paper. The most influencing classes of diseases are selected by sensitivity analysis. It is proved that Neural Network Models appear to be an adequate tool for mortality structure examination. Some interesting results for males and females total … …American Journal of Applied Sciences, Vol. 3, Issue 2 · 28 Sep 2006 · 7,056 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsA Hybrid Metaheuristic Algorithm for Diseases Classification Using UAV ImagesYagnasree Sirivella, Anuj JainRecent advances in technology are very astounding since they have made it possible to manage and monitor systems remotely. Traditional farming is undergoing a transition towards "smart farming" with the assistance of technological breakthroughs, which include the implementation of intelligent irrigation systems and the remote monitoring of the development of crops. In particular, the Unmanned Aerial Vehicle plays a significant … …Journal of Computer Science, Vol. 19, Issue 10 · 11 Sep 2023 · 5,251 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsArabic Named Entity Recognition Using Artificial Neural NetworkNaji F. Mohammed, Nazlia OmarProblem statement: Named Entity Recognition (NER) is a task to identify proper names as well as temporal and numeric expressions, in an open-domain text. The NER task can help to improve the performance of various Natural Language Processing (NLP) applications such as Information Extraction (IE), Information Retrieval (IR) and Question Answering (QA) tasks. This study discusses on the Named Entity … …Journal of Computer Science, Vol. 8, Issue 8 · 16 Jul 2012 · 8,676 accessesView PDF Cite

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 · 749 accessesView PDF Cite

Research ArticleOpen accessIn the abstractLeveraging Modified Cascaded Fully Convolutional Neural Networks and Optimized Swin U-Net for Liver Lesion PredictionSugandha Chakraverti, Tejaswi Khanna, Vijay ShuklaLiver lesions are abnormal growths that can develop for various reasons, some of which are noncancerous (benign) while others are cancerous. Machine learning and, deep learning techniques are employed for liver health assessment and lesion detection, but the quality and, diversity of training data can hinder the performance, leading to overfitting or underfitting. These models often need extensive pre-processing and … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 372 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAn Efficient Cluster Head Selection in IoV-Enabled VANETs Using a Federated Diffusion Convolutional Recurrent Neural Networks FrameworkP Subhash, Madana Srinivas, A. Ranjith et al.The IoV enables the formation of VANETs that require a strong selection of CHs for effective communication within high-velocity changing traffic scenarios. Existing approaches often face issues related to scalability, privacy, and adaptability. To meet the aforementioned urgent needs, we design a decentralized scheme for intelligent CH selection based on Federated Learning with Diffusion Convolutional Recurrent Neural Networks (DCRNNs). According … …Journal of Computer Science, Vol. 22, Issue 10 · 1 Oct 2026 · 599 accessesView PDF Cite

Research ArticleOpen accessIn the abstractTAGN-IDC: Implicit Discrete Constraints for Tsunami Aware Graph Neural Networks in Spatial Evacuation RoutingSularno, Wendi Boy, Putri Anggraini et al.Tsunami evacuation route requires rapid identification of safe evacuation paths under dynamically changing hazard conditions. A major challenge is incorporating hard binary road-blockage constraints caused by tsunami inundation while maintaining end-to-end differentiability for deep learning models. Existing approaches commonly rely on continuous relaxations or stochastic sampling techniques, which either compromise physical feasibility or increase computational complexity. This study proposes the … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 704 accessesView PDF Cite

Research ArticleOpen accessIn the abstractMorphological Database and Quantification of Liberica Coffee Beans Using a Hybrid CNN ModelDioneces O. Alimoren, Francis G. Balazon, Jonnah R. Melo et al.Traditional evaluation of Liberica coffee (Kapeng Barako) in Batangas is commonly performed through manual visual inspection and sensory judgment, which are slow, subjective, and difficult to reproduce across farms, buyers, and grading personnel. These limitations can lead to inconsistent quality classification, weak traceability, and reduced bargaining power for local producers. This study develops and validates a web-based morphological analysis system … …Journal of Computer Science, Vol. 22, Issue 8 · 24 Aug 2026 · 1,337 accessesView PDF Cite