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557 articles for “Neural network”
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Research ArticleOpen accessIn the abstractIntelligent Multi Model Ensemble for Engagement PredictionFahmida Begum, K Ulaga PriyaFor intelligent educational systems, the ability to monitor and respond to student engagement in real time is essential for enhancing learning outcomes. However, existing models often lack adaptability and practical deployment potential, as they depend on single data modalities, rigid ensemble mechanisms, and post-session analysis. This study introduces an intelligent multimodal ensemble framework designed to address these challenges by predicting … …Journal of Computer Science, Vol. 22, Issue 4 · 28 Apr 2026 · 1,853 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Models for Predicting Stock Closing Prices in the Saudi Stock MarketAreej Alhumaidi, Hoda A. AbdelhafezFinancial time series data are inherently volatile and nonlinear, presenting considerable challenges in accurately forecasting stock market trends. This study aims to predict the closing prices of companies listed on the Saudi stock market by analyzing historical data spanning from 2013 to 2023. To this end, four deep learning models were employed-Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), Gated Recurrent … …Journal of Computer Science, Vol. 22, Issue 4 · 22 Apr 2026 · 1,363 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comprehensive Review of Medical Image Denoising: Techniques, Challenges, Applications and Future DirectionsMohit Sharma, Ayush Dogra, Anita Gupta et al.The concept of noise reduction in medical images plays a vital role in improving image quality and accuracy associated with diagnosis, and facilitating reliable automated analysis. This survey presents a structured overview of medical image denoising, beginning with foundational definitions and noise models for modalities such as MRI and CT. We critically evaluate persistent gaps, including the limited generalizability of … …Journal of Computer Science, Vol. 22, Issue 3 · 28 Mar 2026 · 1,861 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intelligent System for Cardiovascular Disease Prediction Using Deep LearningDeepika Arora, Deepak Dudeja, B K AgrawalHeart disease remains among the major causes of death in the world. Hence, accurate and reliable prediction schemes are key. To detect the presence of diseases in early stages, data mining and deep learning algorithms offer powerful tools to determine important trends in large and complex data. To enhance the prediction of cardiac diseases, this paper proposes a hybrid deep … …Journal of Computer Science, Vol. 22, Issue 2 · 9 Mar 2026 · 1,613 accessesView PDFCite
Research ArticleOpen accessIn the abstractRecognizing Sign Language Gestures Using a Hybrid Spatio-Temporal Deep Learning ModelMeryem Cherrate, My Abdelouahed Sabri, Ali Yahyaouy, Abdellah AarabRecognizing gestures in American Sign Language (ASL) from video data presents significant challenges due to the intricate combination of hand gestures, facial cues, and body motion. In this work, we introduce a hybrid deep learning framework that integrates Convolutional Neural Networks (CNNs) for extracting spatial characteristics with Long Short-Term Memory (LSTM) networks for capturing temporal sequences. The model was trained … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,056 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmotion Recognition from Microblog Managing Emoticon with Text and Classifying using 1D CNNMd. Ahsan Habib, M. A. H. Akhand, Md. Abdus Samad KamalMicroblog, an online-based broadcast medium, is a widely used forum for people to share their thoughts and opinions. Recently, Emotion Recognition (ER) from microblogs is an inspiring research topic in diverse areas. In the machine learning domain, automatic emotion recognition from microblogs is a challenging task, especially, for better outcomes considering diverse content. Emoticon becomes very common in the text … …Journal of Computer Science, Vol. 18, Issue 12 · 7 Dec 2022 · 6,925 accessesView PDFCite
Research ArticleOpen accessIn the abstractANN Based Prediction of Effect of Reinforcements on Abrasive Wear Loss and Hardness in a Hybrid MMCP. Sathyabalan, V. Selladurai, P. SakthivelProblem statement: The reinforcements added to an alloy lead to variation in properties. The content and size of the reinforcement influences the properties of composites. Very little research has been carried out in hybrid composites. Work on hybrid LM6 aluminium alloy metal matrix composites (MMC) with flyash and SiC has been initiated here. The effect of the four parameters, size … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 1 · 31 Mar 2009 · 7,558 accessesView PDFCite
Research ArticleOpen accessIn the abstractDesign and Analysis of a Smart Multi Purpose Electronic Nose SystemMahmoud Z. Iskandarani, Nidal F. ShilbayehAn electronic nose system for multi application purposes is designed and tested. Our hardware design allows various types of sensors to be used for different applications. The system is capable of being interfaced to both analog and digital instruments with special filtering devices that isolate the system from surrounding signals. The design of the system is distinguished through the use … …Journal of Computer Science, Vol. 1, Issue 1 · 31 Mar 2005 · 6,942 accessesView PDFCite
Review ArticleOpen accessIn the abstractHealthcare Driven by Big Data AnalyticsCheryl Ann Alexander, Lidong WangText messages and social network posts are often included in big data and are frequently invaluable sources of health data. When machine learning or data mining is used, it is important to perform an automatic process for integrating all available and related health data. Artificial Neural Network (ANN) is one of the machine learning methods flexible in using algorithms to … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 3 · 28 Sep 2018 · 7,403 accessesView PDFCite
Research ArticleOpen accessIn the abstractHematologic Cancer Cell Detection and Classification Using Optimized VGG-19 with Stratified K-fold Cross-ValidationHema Patel, Himal Shah, Gayatri Patel, Atul PatelThe most prevalent pediatric blood malignancy is acute lymphoblastic leukemia (ALL). ALL is a lethal disease in which patients have a lower survival rate. Its prompt detection and precise categorization are essential for successful treatment. Manual microscopic diagnosis is laborious, prone to mistakes, and heavily reliant on specialized knowledge. With stratified 7-fold cross-validation, which assures an equal ratio of normal … …Journal of Computer Science, Vol. 21, Issue 11 · 24 Dec 2025 · 1,822 accessesView PDFCite