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185 results for “In-Network Processing”
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Research ArticleOpen accessIn the keywordsA Review on Recent Research and Implementation Methodologies on Medical Image SegmentationS. K. Somasundaram, P. AlliProblem statement: Image segmentation plays a very important role in digital imaging applications for classifying the anatomical structures and other Regions of Interest. Segmentation refers to the process of identifying and isolating the surface and regions of the digital image which corresponds to the structural units. Approach: In the past few decades, many methods have been proposed to segment the … …Journal of Computer Science, Vol. 8, Issue 1 · 4 Nov 2011 · 7,117 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDynamic Bayesian Networks in Classification-and-Ranking Architecture of Response GenerationAida Mustapha, Md. Nasir Sulaiman, Ramlan Mahmod, Mohd. Hasan SelamatProblem statement: The first component in classification-and-ranking architecture is a Bayesian classifier that classifies user utterances into response classes based on their semantic and pragmatic interpretations. Bayesian networks are sufficient if data is limited to single user input utterance. However, if the classifier is able to collate features from a sequence of previous n-1 user utterances, the additional information may … …Journal of Computer Science, Vol. 7, Issue 1 · 27 Dec 2010 · 8,104 accessesView PDFCite
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 PDFCite
Research ArticleOpen accessIn the abstractOptimized Wireless Sensor Network Clustering Using a Hybrid Firefly–Bat Algorithm (HFBA)J. Jegan, Senthil kumar P, S. Saravanakumar et al.Wireless Sensor Networks (WSNs) are composed of numerous sensor nodes that collaborate to observe and evaluate various environmental parameters, transmitting the data to a central base station. Each node is equipped with a unique transmitter, receiver, and processor to facilitate sensing, processing, and communication. These networks are often installed in extremely remote and inaccessible areas. A significant challenge arises from … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,431 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized WFST-Based ASR for Arabic: Balancing Memory, Speed, and AccuracyWael A. Sultan, Mourad S. Semary, Sherif M. AbdouWeighted Finite-State Transducers (WFSTs) have revolutionized Automatic Speech Recognition (ASR) by enabling significantly faster decoding speeds compared to traditional systems that build the search space progressively. However, applying WFSTs to morphology-rich languages such as Arabic presents challenges due to the large vocabulary, resulting in extensive networks that exceed the memory capacity of standard CPUs. This study introduces various strategies to … …Journal of Computer Science, Vol. 22, Issue 2 · 23 Feb 2026 · 1,442 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmploying Hybrid Serial Cascaded Adaptive Network for Anomaly Detection and Prevention in IoT Time Series Data With Optimal Interdomain RoutingKante Satyanarayana, K. VenkateshNowadays, emerging Internet of Things (IoT) in data processing becomes interested research topic and is used for various applications. This varies from big data processing and analytics for accumulating entire sensor data to detect and generate long-term trends. Nevertheless, this results in the requirement for resources like the execution of power, memory, and bandwidth, in which resource-constrained IoT tools suffers … …Journal of Computer Science, Vol. 22, Issue 1 · 21 Feb 2026 · 1,466 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Dynamic Lifelong Learning Network for Real-Time Stock Prediction With Reinforcement TuningTalent Mawere, Selvaraj Rajalakshmi, Venu Madhav Kuthadi, Otlhapile DinakanyaneCompanies and investors require accurate market forecasting to make more informed decisions. Traditional methods for predicting stock market performance have become less useful considering the dynamic and volatile nature that characterizes stock markets today. In this paper, we propose an innovative Dynamic Lifelong Learning Network for stock market prediction. The model incorporates a hybrid convolutional long short-term memory with an … …Journal of Computer Science, Vol. 22, Issue 2 · 20 Feb 2026 · 1,822 accessesView PDFCite
Research ArticleOpen accessIn the abstractIdentification 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 PDFCite
Research ArticleOpen accessIn the abstractRobust Adversarial Attack Detection via Generative Adversarial Network With Residual Multi-Layer Aggregation Based Contrastive Loss FunctionAmudha Gopalakrishnan, Nalini JosephAdversarial attacks in medical imaging refer to subtle modifications to images that mislead diagnostic systems, resulting in inaccurate diagnoses and assessments. These attacks exploit vulnerabilities in image processing, leading to misclassification or altered visual features that often go unnoticed. This raises serious concerns about the security and reliability of medical diagnosis, directly impacting clinical decision-making and patient safety. This research … …Journal of Computer Science, Vol. 22, Issue 1 · 10 Feb 2026 · 1,742 accessesView PDFCite
Research ArticleOpen accessIn the abstractAuto Weight Dilated Convolutional Ensemble Network for the Severity Analysis of Lung Cancer in CT ImagesL. Sandhya, K. MarimuthuLung cancer is one of the world's leading causes of morbidity and mortality; improving patient outcomes requires an early and precise diagnosis. Lesion and tumor segmentation remains a challenging task in CT images due to their inherent imaging limitations, such as the small size of nodules, heterogeneous textures, blurry boundaries, and adjacent structures, leading to misclassification and difficulty in delineating … …Journal of Computer Science, Vol. 22, Issue 1 · 9 Feb 2026 · 1,541 accessesView PDFCite