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145 articles for “Deep Learning Models”

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Research ArticleOpen accessIn the abstractA Collaborative Prediction of Presence of Arrhythmia in Human Heart with Electrocardiogram Data using Machine Learning Algorithms with AnalyticsSelvaraj Rajalakshmi, Kuthadi Venu MadhavHuman heart is the major organ of human being which could fail the other systems in the body at the same time. Hence predicting heart disease is one of the challenging researches that requires meticulous analysis of heart rhythms properly. The irregular heart rhythms or beat is referred to as the Arrhythmia where heart rhythms with low or high rates … …Journal of Computer Science, Vol. 15, Issue 2 · 22 Feb 2019 · 7,513 accessesView PDFCite
Review ArticleOpen accessIn the abstractMultimodal Sentiment Analysis: A Comparison StudyIntisar O. Hussien, Yahia Hasan JazyahSentiments and emotions play a pivotal role in our daily lives. They assist decision making, learning, communication and situation awareness in human environments. Sentiment analysis is mainly focused on the automatic recognition of opinions’ polarity, as positive or negative. Nowadays, sentiment analysis is replacing the old web based survey and traditional survey methods that conducted by deferent companies for finding … …Journal of Computer Science, Vol. 14, Issue 6 · 11 Jun 2018 · 9,911 accessesView PDFCite
Research ArticleOpen accessIn the abstractArabic Speech Pathology Therapy Computer Aided SystemZ. A. Benselama, M. Guerti, M. A. BencherifThis article concerns a computer aided pathological speech therapy program, based on speech models such as the hidden Markov model and artificial intelligence networks, in order to help persons, suffering from language pathologies, follow a correction learning process, with different interactive feedbacks, aiming to evaluate the degree of evolution of the illness or the therapy. We dealt with the Arabic … …Journal of Computer Science, Vol. 3, Issue 9 · 30 Sep 2007 · 6,937 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAdvancing Digital Forgery Detection: A Comparative Analysis of U-Net, Buster Net, Efficient B0+ U-Net, and VGG 16+ U-Net ModelsPreeti Dhiman, Usha ChauhanForgery Detection in the area of digital images is indispensable for insuring authenticity, particularly in detecting Copy-Move, Splicing. In this research, a meticulous analysis of latest learning architectures i.e. U-Net, Buster Net, Efficient B0+U-Net and VGG16+U-Net are compared for the detecting these types of forgeries. U-Net is popular due to its potent segmentation capabilities to provide pixel-level forgery localization while … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 394 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordLightweight Deep Learning Model for TFT-LCD Pixel Defect Detection Using MobileNetV2J. Sheikshabjan, K. Dhanakodi, A.T. Rajamanickam et al.The proposed methodology aims to achieve high classification accuracy while maintaining computational efficiency and minimizing inference latency, making it highly suitable for real-time industrial inspection scenarios. This study evaluated five traditional transfer learning models (VGG16, ResNet50, MobileNetV2, Xception, and InceptionV3) for comparison in pixel defect detection. MobileNetV2-based implementation demonstrated a competitive average test accuracy of 0.9916, outperforming several baselines while … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 683 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordImplementing a Hybrid VMD–BiTCN–BiGRU Architecture With Intelligent Optimization for Agricultural Commodity Price Prognostication in Gujarat MarketsJignesh Hirapara, Ratnesh Kumar Namdeo, Ankit Kumar Dubey et al.In the agricultural sector, the prices of pulses require adequate forecasting to plan farming activities, store and market, and guide policy-making. However, the pulse price series is highly volatile, seasonal, nonstationary, and nonlinear, and thus conventional linear time series models are not necessarily very effective. In the suggested framework, the raw price data series is decomposed using Variational Mode Decomposition … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Aug 2026 · 1,042 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAnimal Health Prediction Using Hybrid CNN Based BiLSTM Classification Model: A Deep Learning ApproachJ. Rathi, A. SumathiAccurate prediction of animal diseases is vital in veterinary medicine, as it can substantially enhance animal health outcomes and mitigate economic losses, making it a critical task that warrants attention and innovative solutions. This paper proposes a novel approach to animal condition classification, leveraging an Auto-encoder-based feature selection process and an Improved Hybrid Convolutional Neural Networks (CNN) with Bidirectional (Bi-LSTM) … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,488 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Hybridized BERT-Based Approach for Crime News Collection and Classification from Online NewspapersAshour Ali, Shahrul Azman Mohd Noah, Lailatul Qadri Zakaria, Saeed Amer Al AmeriCrime news analysis is crucial for understanding criminal activity, enhancing public safety, and informing policy decisions. The exponential growth and unstructured nature of online news articles, however, present significant challenges for efficient and accurate information extraction. This study aims to enhance the efficiency and accuracy of crime news data collection and classification through advanced Natural Language Processing (NLP) techniques and … …Journal of Computer Science, Vol. 21, Issue 9 · 16 Oct 2025 · 2,297 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordXAI_MLPCNN: A Novel Explainable AI-Based Deep Learning Framework for Stress IdentificationFateh Bahadur Kunwar, Rakesh Kumar Yadav, Hitendra Singh, Nitin TripathiOver the past ten years, there has been a lot of emphasis focusedon the development of Artificial Intelligence (AI) and Machine Learning(ML)-based mental health treatments. To increase practitioners' and patients'trust in AI applications, AI systems need to explain their actions. This iscalled Explainable AI (XAI). While significant progress has been achievedin stress prediction models, XAI has not advanced as much. … …Journal of Computer Science, Vol. 21, Issue 5 · 6 May 2025 · 6,173 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordDifferSqueezeNet: A Leaner Defect Detection ModelJose Joao Manrique Franco, Marcelo RudekIn the industrial environment, the inherent limitations of manual inspection have caused the ascent of automated computer vision systems that aim to match or surpass human performance. In this context, the artificial intelligence field has been interested in defect detection with the creation of many machine learning techniques, focusing on Unsupervised and Semi-supervised learning methods. Since most of these methods … …Journal of Computer Science, Vol. 21, Issue 3 · 4 Feb 2025 · 5,734 accessesView PDFCite