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263 results for “Model Optimization”
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Research ArticleOpen accessIn the abstractCloud Privacy Preservation Using Improved Squeezenet Based Data Sanitization and Improved Lyrebird Optimization-Based Optimal Key GenerationSmita Sharma, Sanjay TyagiMaintaining privacy in the cloud is critical, which implies reliable and effective models that are adapted to the difficulties presented by cloud settings. This paper introduces a comprehensive privacy preservation model tailored specifically for cloud environments, comprising five important phases such as data acquisition, normalization, feature extraction, sanitization and restoration. It begins with the meticulous collection of data from diverse … …Journal of Computer Science, Vol. 21, Issue 7 · 20 Aug 2025 · 3,190 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Antigenic Peptides Using a Multi-Level Transformer Model with Enhanced Feature SelectionAshwini S., Minu R. I., Jeevan KumarThis Antigenic Peptide (APs) prediction is one of the most important roles to improve vaccine design and interpret immune responses. This paper develops a Multi-Level Pooling-based Transformer model, which improves the accuracy and efficiency of predicting T-cell epitopes. The model utilizes peptide sequences from the Immune Epitope Database, employing a refined Kolaskar and Tongaonkar algorithm for feature extraction and a … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,443 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization-Based Feature Selection and Ensemble Machine Learning Algorithms for Breast Cancer ClassificationSatyabrata Patro, Jyotirmaya Mishra, Bhavani Sankar PandaBreast cancer, which originates in a woman's breast tissue, is acknowledged to be a significant study topic in the medical field. For a long time, there has been a serious concern with the classification of breast cancer. Thus, to effectively categorize the breast cancer dataset, machine learning methods are designed and implemented. In previous research, the algorithms have classification accuracy … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,172 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Designing Framework for Ant Colony Algorithm for Managing Cognitive InsomniaRoqia Rateb, Amal Shorman, Ahmad Sami Al-Shamayleh et al.Insomnia, a condition characterized by poor sleep quality, significantly impacts cognitive function, mood, and overall well-being. Traditional treatments like medication and psychological therapies, while effective, often come with limitations such as high costs and limited scalability. This study addresses these challenges by proposing an Ant Colony Optimization (ACO) algorithm-based approach to create a dynamic support network for individuals suffering from … …Journal of Computer Science, Vol. 21, Issue 7 · 7 Jul 2025 · 3,518 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Conceptual Framework for Efficient and Sustainable Pruning Techniques in Deep Learning ModelsNyalalani Smarts, Rajalakshm Selvaraj, Venumadhav KuthadiThis research paper proposes a conceptual framework and optimization algorithm for pruning techniques in deep learning models, its focus is on key challenges such as model size, computational efficiency, inference speed and sustainable technology development. The aim of the framework is to transition from large neural networks to sparse, efficient models, indicating the benefits of pruning in improving model scalability … …Journal of Computer Science, Vol. 21, Issue 5 · 26 Apr 2025 · 5,268 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Optimization to Trust Enhanced Secure Routing Optimization with IABC and CGWAA for MANETYuvaraja Panneer Selvam, Suganthi PerumalRouting in Mobile Ad Hoc Networks (MANET) presents significant challenges due to the dynamic nature of network topology. Optimal route selection and efficient route discovery are matched by effective routing in MANET. This study proposes a Hybrid Optimization to Trust-Enhanced Secure Routing Optimization (HO-TESRO) designed to address these challenges in IoT environments by integrating metrics such as link stability, bandwidth, … …Journal of Computer Science, Vol. 21, Issue 4 · 19 Mar 2025 · 4,983 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Attention-Based Stacked Bi-LSTM Model for Automated MultiImage CaptioningPaspula Ravinder, Saravanan SrinivasanIn recent days, the process of medical image captioning is become a prominent field. The distinct characteristics of medical imaging data provide a number of challenges when captioning medical images. Also, the variability in image modalities makes it difficult to generate an effective captioning process. Thus, the proposed study aims to design a novel Multi-image Captioning Hybrid Attention Model to … …Journal of Computer Science, Vol. 21, Issue 4 · 8 Mar 2025 · 5,157 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Machine Learning Approach to Predictive Analytics in Precision Agriculture for Sustainable Crop OptimizationJignesh Kariya, Pankaj MudholkarDriven by data-enabled technologies, precision agriculture is evolving into an innovative way to increase agricultural productivity and sustainability. Conventional agricultural practices face several challenges, such as poor soil quality, inappropriate crop selection, improper resource utilization, and unpredictable climate conditions. To address these limitations, this paper proposes a hybrid machine learning framework for sustainable crop optimization and predictive analysis in precision … …Journal of Computer Science, Vol. 22, Issue 10 · 10 Oct 2026 · 865 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 abstractSmart and Secure Anomaly Detection in IoT Using Quantum Inspired Kernel Ensemble LearningAbrar M. AlajlanThe exponential growth of the Internet of Things networks has greatly increased the attack surface for cyber threats, necessitating the use of strong and perceptive anomaly detection systems. Traditional intrusion detection systems often struggle with high false alarm rates, limited generalization, and inefficiency in processing high-dimensional heterogeneous IoT data. To address this issue, a novel Hybrid Quantum-Enhanced Kernel Ensemble Learning … …Journal of Computer Science, Vol. 22, Issue 3 · 12 Mar 2026 · 1,762 accessesView PDFCite