Research ArticleOpen accessIn the keywordsA 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 abstractMitigating the Evidence-Related Factors in Automated Fact-CheckingAruna Shankar, Narayanan Kulathuramaiyer, Johari Bin Abdullah, Muthukumaran PakkirisamyThe rapid proliferation of digital misinformation highlights the urgent need for robust automated fact-checking systems that can accurately distinguish truth from falsehood. A persistent challenge for these systems is the occurrence of false positives, where truthful information is incorrectly flagged as misleading due to limitations in evidence assessment, including insufficient evidence, logical inconsistencies, and conflicting information. This research introduces a … …Journal of Computer Science, Vol. 21, Issue 3 · 13 Feb 2025 · 5,992 accessesView PDFCite