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149 articles for “Neural Network Classification”
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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 · 1,344 accessesView PDFCite
Research ArticleOpen accessIn the abstractGait Analysis Combining Sports Biomechanics and ImagingChao ZhuAiming at the problems of marker positioning error, soft tissue interference, and insufficient personalized modeling ability in traditional gait analysis, this study proposes a gait assessment method that integrates sports biomechanics and multimodal imaging analysis. Firstly, based on the public OU-ISIR gait database, a Convolutional Neural Network (CNN) is used to extract the key gait features in the human silhouette … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 2 · 20 Jul 2026 · 858 accessesView PDFCite
Research ArticleOpen accessIn the abstractEpileptic Seizure Detection from EEG Signal Using Progressive Channel Selection and Deep LearningSuraiya Akter Mumu, Shupta Das, M. A. H. Akhand et al.Epileptic Seizures (ES), marked by abrupt abnormal electrical discharges in the brain, represent the primary symptom of epilepsy, making timely and accurate detection critical because of their unpredictable recurrence and potentially severe consequences. The Electroencephalogram (EEG), a widely used, non-invasive, and economical method for monitoring brain activity, plays a key role in automated ES detection through Machine Learning (ML) and … …Journal of Computer Science, Vol. 22, Issue 6 · 8 Jul 2026 · 1,409 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Crow Search Optimization Based Feature Selection With Optimal DNN for Big Data ClassificationC. Mahesh, J. Ruby Elizabeth, S. Gnana Selvan et al.Big data analytics has become popular due to its applicability in various real-time applications. To attain better performance, big data can be analyzed using the machine learning and deep learning models at recent times, various domains have started to deal with big dataset which involves numerous sets of features. Repetitive and unwanted features, which reduces the classification performance can be … …Journal of Computer Science, Vol. 22, Issue 6 · 30 Jun 2026 · 1,257 accessesView PDFCite
Review ArticleOpen accessIn the abstractImproving Classification and Clustering Accuracy of Palembang Duku Fruit Quality via CNN-K-Means IntegrationHenny Hartono, Francka Sakti Lee, Herlina Herlina et al.Duku Palembang (Lansium domesticum Corr.) is a leading commodity from South Sumatra with high economic value. The quality assessment process for duku has traditionally relied on manual visual inspection, which is subjective, time-consuming, and inconsistent, especially at large production scales. This study proposes an integrative framework combining Convolutional Neural Network (CNN) and K-Means Clustering to improve the accuracy of classification … …OnLine Journal of Biological Sciences, Vol. 26, Issue 2 · 8 May 2026 · 1,479 accessesView PDFCite
Research ArticleOpen accessIn the abstractUncertainty-Aware Ensemble Models for Improved Defect Detection in Noisy DataMadhavi Perla, Gadi Lava Raju, A Radha Krishna et al.Software defect prediction plays a crucial role in ensuring software quality and reliability, especially as modern systems become more complex and data rich. This study introduces an uncertainty-aware ensemble learning framework aimed at improving defect classification performance in noisy and imbalanced datasets, particularly those from the PROMISE and NASA KC1 repositories. The proposed model integrates multiple classifiers in a multi-learner … …Journal of Computer Science, Vol. 22, Issue 4 · 27 Apr 2026 · 1,549 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 · 1,898 accessesView PDFCite
Research ArticleOpen accessIn the abstractEdge Computing Enabled Human Activity Recognition (ECEHAR) Using LSTM and CNNSuresh Kumar, M Y. Mohamed ParveesHuman Activity Recognition (HAR) is an important research area for various application domains such as healthcare, gaming, telemonitoring, and sports. However, executing HAR algorithms on remote servers or in the cloud have challenges in terms of high latency, increased bandwidth demand, and high energy consumption. Moving the computation to edge-assisted HAR is more effective and flexible solution to address the … …Journal of Computer Science, Vol. 22, Issue 3 · 6 Mar 2026 · 1,584 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 · 2,167 accessesView PDFCite
Research ArticleOpen accessIn the abstractBlockchain-Enabled Decisive Red Fox Optimizer-Based Feature Selection With Deep Learning-Based Intrusion Detection SystemC. Ananth, S. Sathiyarani, N. MohananthiniRecently, Intrusion Detection Systems (IDS) using Deep Learning (DL) models become useful in accomplishing network security. The selected features serve as input to the DL model, which is trained on labelled datasets to learn intrinsic patterns distinguishing malicious from normal network behaviour. DL techniques like Convolutional Neural Networks (CNN) are usually utilized. The seamless combination of Public Blockchain (BC) technology … …Journal of Computer Science, Vol. 21, Issue 12 · 20 Jan 2026 · 1,722 accessesView PDFCite