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Research ArticleOpen accessIn the abstractExplainability Aware Heterogeneous Temporal Graph Transformer for Automated Genetic Disorder Detection from Genomic DataPuvaneswari Subramaniapillai, Indirani Govindasamy, Revathy GurumurthyGenetic disorders affect millions worldwide, posing major challenges for accurate diagnosis and effective treatments. New developments in genomic technologies, especially Next-Generation Sequencing (NGS), have enhanced the classification of genetic modification and improved diagnostic abilities. Moreover, the Machine Learning (ML) and Deep Learning (DL) methods emerged as efficient tools for evaluating the intricate genomic data and determining the patterns, which can … …Journal of Computer Science, Vol. 22, Issue 11 · 14 Oct 2026 · 581 accessesView PDFCite
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 · 774 accessesView PDFCite
Research ArticleOpen accessIn the abstractContext Tamil Llama-QA: A Question and Answering Framework for Semantic Information Retrieval Using Tamil Large Language ModelJeevit Davidson S., M. MuraliThe Question Answering System (QA) is essential for effectively retrieving and providing relevant information, and its performance is heavily reliant on the efficiency of information retrieval mechanisms. As the volume of information within the corpus continues to grow, the complexity of generating accurate and pertinent answers also increases substantially. This challenge is particularly significant when designing QA systems for regional … …Journal of Computer Science, Vol. 22, Issue 10 · 7 Oct 2026 · 456 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetermination of Crop Yield Detection and Prediction With Multimodal Data Using Fusion TechniquesKutlwano Sedimo, Rajalakshmi Selveraj, Venumadhav Kuthadi, Thulaganyo DimakatsoMost often, soil, environmental, and agronomic data are used in pieces, hence limiting the performance of crop selection and yield forecasting. This study develops an integrated, fusion-based framework that combines soil image classification, environmental feature analysis, and input-driven yield prediction to support precise agricultural decision-making. The system consists of three major modules: (i) a CNN for the classification of soil … …Journal of Computer Science, Vol. 22, Issue 10 · 5 Oct 2026 · 494 accessesView PDFCite
Research ArticleOpen accessIn the abstractBenchmarking Lightweight Deep Learning Models for Field Based Sorghum Leaf Disease DetectionPrince Daughin Ngqabutho NcubeSorghum is a climate-resilient cereal crop central to food and livelihood security across Southern Africa, yet its productivity is frequently reduced by foliar diseases that smallholder farmers struggle to diagnose reliably in the field. While deep learning has demonstrated strong potential for automated plant disease identification, sorghum remains underrepresented in the literature, and no prior study has provided a comprehensive, … …Journal of Computer Science, Vol. 22, Issue 10 · 29 Sep 2026 · 548 accessesView PDFCite
Research ArticleOpen accessIn the abstractDual-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 · 632 accessesView PDFCite
Research ArticleOpen accessIn the abstractMulti-FOM: A Unified Multimodal Deep Learning Framework for Intelligent Pre-Harvest Papaya Classification and Crop ValorisationSovers Singh Bisht, Sanjeev Thakur, Sanjeev PanwarIntelligent pre-harvest crop assessment has become an essential component of precision agriculture, where accurate crop quality evaluation enables informed decision-making and sustainable crop management. However, existing multimodal frameworks often exhibit limited data diversity and insufficient cross-modal semantic interaction, reducing the reliability of intelligent crop valorisation. Address these limitations, this paper proposes a Multimodal Focal-Mamba Optimized Valorisation Model (Multi-FOM), a unified … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 678 accessesView PDFCite
Research ArticleOpen accessIn the abstractUMPM-Net: A Multimodal Deep Learning Framework for Colorectal Cancer PrognosisK. Muthuchamy, S K. Piramu PreethikaColorectal cancer (CRC) is one of the most common cancers worldwide, for which early prediction of patient outcomes is important for personalised treatment planning and to improve survival. However, current prediction systems are limited in the fact that they are based on single-modality data and cannot capture the complex interactions between clinical, imaging, and genomic factors. To overcome these shortcomings, … …Journal of Computer Science, Vol. 22, Issue 9 · 20 Sep 2026 · 621 accessesView PDFCite
Research ArticleOpen accessIn the abstractChronic Lung Disease Identification in Chest CT Scans Through Hybrid Deep Transfer Learning FrameworkGarima Jain, Amit Kumar Goel, Rahul KumarAccurate and timely diagnosis is essential for successful treatment of chronic pulmonary conditions, particularly lung tumours. To capture more complicated pathological characteristics, diagnostic algorithms based on current data sets are restricted to using older databases and single branch systems. This research introduces a new solution: A hybrid deep learning model applied to a recently released quantitative database of CT scans … …Journal of Computer Science, Vol. 22, Issue 8 · 9 Sep 2026 · 657 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Review of Artificial Intelligence and Deep Learning Approaches for Cocoa Pod Disease DetectionHenry Techie-Menson, Michael Asante, Yaw Marfo Missah et al.Cocoa pod diseases destroy an estimated 700,000 metric tons of cocoa annually, threatening 40–50 million smallholder farmers across tropical regions. Accurate field diagnosis remains constrained by symptom similarity, labour-intensive scouting, and limited specialist access in remote communities. This paper presents a PRISMA-guided systematic review of 25 peer-reviewed studies on automated cocoa pod disease detection and classification (2016–2026), addressing architectural approaches, … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 743 accessesView PDFCite