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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 PDFCite
Research ArticleOpen accessIn the abstractExplainable MedAttn-ResNet50 for Automated Kidney Tumor Classification from CT Images With Grad-CAM VisualizationD. Vetrithangam, Pramod Kumar, Shilpasree S. et al.Kidney tumor classification from CT imaging remains challenging due to CT-specific intensity variations, tumor heterogeneity, and limited clinically meaningful interpretability in existing deep learning models. To address these limitations, we propose an Explainable MedAttn-ResNet50 framework that integrates radiology-driven preprocessing, multi-scale feature extraction, and medical attention mechanisms within a unified architecture. The preprocessing pipeline applies radiology-inspired intensity normalization, contrast enhancement, and … …Journal of Computer Science, Vol. 22, Issue 8 · 13 Aug 2026 · 1,120 accessesView PDFCite
Research ArticleOpen accessIn the abstractUzNER: A Human-Reviewed Benchmark for Uzbek Named Entity Recognition With Gazetteer-Augmented Transformer ModelsBobur Saidov, Vladimir Barakhnin et al.UzNER-100K is a large-scale human-reviewed benchmark for Uzbek named entity recognition with 100,000 training sentences, 18 fine-grained entity types and 200,083 entity mentions across 114,269 sentences in total. The corpus was constructed through an LLM-assisted, expert-reviewed annotation pipeline that achieved strong reliability on the main audit subset while substantially reducing corpus-construction effort. The benchmark includes a standard test split, a … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,308 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Machine Learning Models to Predict Student Academic Performance Using Structured Educational DataHardik Ishwarbhai Patel, Dharmendra PatelThis study analyses the use of machine learning for predicting the academic performance of students using their academic information from the institution, combined with socio-economic information that comes from outside sources. The collection of information is done using structured questionnaires as well as through data extraction from the Student Information System (SIS). To increase the reliability of models built, a … …Journal of Computer Science, Vol. 22, Issue 5 · 26 May 2026 · 1,419 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Integrated Machine Learning Framework for Citrus Grading and Yield Prediction Using Classifier-Informed RegressionLydia Dede Obeng, Isaac O. OsunmakindeAgriculture remains a cornerstone of human sustenance, yet accurate citrus fruit grading and yield predictions remain significant challenges due to visual similarities between varieties such as oranges and grapefruits. This includes the inefficiencies of manual grading. This study presents a new dual-function machine learning system that integrates classification and regression to simultaneously grade citrus fruits and forecast crop yields. This … …Journal of Computer Science, Vol. 22, Issue 4 · 24 Apr 2026 · 1,891 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Context-Aware Temporal Convolutional Network for Water Replacement Prediction in Catfish Biofloc Ponds With Imbalanced Event HandlingYaddarabullah, Inanpi Hidayati Sumiasih, Mutiara Dewi PuspitawatiWater replacement is a biologically critical yet under-automated decision in biofloc-based aquaculture systems. Mistimed actions can destabilize microbial ecosystems, elevate fish mortality, and compromise sustainability through excessive water usage. Traditional rule-based heuristics often fail to account for the nonlinear and multiscale dynamics of pond environments. To address this, we propose a Context-Aware Temporal Convolutional Network (CA-TCN), a rare-event classification framework … …Journal of Computer Science, Vol. 22, Issue 3 · 5 Mar 2026 · 1,664 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Traffic Light System Using Convolutional Neural Network to Optimize Vehicle Flow in IndonesiaBhustomy Hakim, Fergie Joanda Kaunang, Yemima Monica Geasela, Regina HillaryTraffic congestion remains a persistent challenge in major Indonesian cities due to rapidly increasing vehicle density and the continued reliance on fixed-time traffic signal scheduling. This study aims to develop an intelligent traffic light system that dynamically adjusts sequencing based on real-time road conditions. A dataset of 902 CCTV images was collected from intersections in six large cities across Indonesia, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,155 accessesView PDFCite
Research ArticleOpen accessIn the abstractUsing Deep Learning to Support Clinical Decision-Making: The Case of Alzheimer’s Disease DiagnosisNawal Mohamed Bahy Eldin, Ghada A. El Khayat, Abeer A. AmerAlzheimer’s disease is a chronic, progressive brain disorder that leads to a gradual decline in memory and cognitive functions. In this study, N-VGG16, an advanced deep learning model, is proposed. The model builds upon the VGG16 architecture, incorporating key enhancements to improve its ability to classify neurodegenerative conditions. The model processes structural neuroimaging data using a refined pipeline that applies … …Journal of Computer Science, Vol. 21, Issue 10 · 11 Dec 2025 · 3,383 accessesView PDFCite
Research ArticleOpen accessIn the abstractReal-Time Endoscopic Image Semantic Segmentation for Efficient Polyp IdentificationM. Al-AsliThe advancement of endoscopic procedures has significantly enhanced diagnostic capabilities in polyp identification and removal, which is critical for colorectal cancer prevention. However, the success of these procedures hinges on the accuracy and speed of real-time image analysis. Traditional image processing methods often fail to provide timely and precise segmentation of endoscopic images. This paper presents the implementation of endoscopic … …Journal of Computer Science, Vol. 21, Issue 10 · 10 Dec 2025 · 2,397 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Software Testing for Test Case Analysis Framework Using ChatGPT with Natural Language Processing and Deep Learning IntegrationAlaa Najmi, Mohamed El-DosukyEffective testing scenarios are necessary to guarantee the dependability and Caliber of software. Conventional techniques for creating these scenarios frequently involve a great deal of manual labor and might not fully cover all software requirements. In order to improve the automation and Caliber of software testing scenario development, this study investigates the combination of Natural Language Processing (NLP) and Deep … …Journal of Computer Science, Vol. 21, Issue 5 · 1 May 2025 · 97,719 accessesView PDFCite