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292 articles for “Deep Learning”
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Research ArticleOpen accessPhrase in the titleImproving the Detection of Mask-Wearing Mistakes by Deep LearningChahinez Mérièm BentaouzaThis study focuses on the detection of wearing mask errors after machine learning by a Multi-Layer Perceptron Mixer (MLP Mixer) applied to protect masks from COVID-19. To combat the spread of the COVID-19 pandemic, facemasks have become an essential accessory, so it's necessary to identify individuals who follow this health protection. In this case, the most successful face-detection method Viola-Jones … …Journal of Computer Science, Vol. 20, Issue 7 · 25 Apr 2024 · 5,195 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleSecuring Mobile Devices from Malware: A Faceoff Between Federated Learning and Deep Learning Models for Android Malware ClassificationNarayan Subramanian, Logesh Ravi, Mithin Jain Shaan et al.Amidst the escalating threats of android malware, urgency mounts to detect issues while safeguarding user privacy. Traditional machine learning and deep learning methods, dealt with scalability challenges and privacy compromises, finding a potential remedy in federated learning. This study introduces a groundbreaking federated learning-based methodology and compares federated learning with traditional deep learning techniques for Android malware classification, employing renowned … …Journal of Computer Science, Vol. 20, Issue 3 · 23 Jan 2024 · 6,284 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleFlock Optimization Algorithm-Based Deep Learning Model for Diabetic Disease Detection ImprovementDivager Balasubramaniyan, Nor Azura Husin, Norwati Mustapha et al.Worldwide, 422 million people suffer from diabetic disease, and 1.5 million die yearly. Diabetes is a threat to people who still fail to cure or maintain it, so it is challenging to predict this disease accurately. The existing systems face data over-fitting issues, convergence problems, non-converging optimization complex predictions, and latent and predominant feature extraction. These issues affect the system's … …Journal of Computer Science, Vol. 20, Issue 2 · 8 Jan 2024 · 5,208 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleLT-LBP-Based Spatial Texture Feature Extraction with Deep Learning for X-Ray ImagesPankaja Lakshmi P., Sivagami M.The novel logarithmic transformation of Local Binary Pattern (LT-LBP) for texture feature extraction is used with Deep Learning (DL) models. The Computational complexity in the DL models asymptotically increases with the data sesssst and the depth of the layers in Convolutional Neural Networks (CNN). Pre-processing the images before training the DL model holds a strong impact on the operation speed … …Journal of Computer Science, Vol. 20, Issue 1 · 18 Dec 2023 · 7,190 accessesView PDFCite
Review ArticleOpen accessPhrase in the titleMasked Face Identification and Tracking Using Deep Learning: A ReviewShahad Fadhil Abbas, Shaimaa Hameed Shaker, Firas A. AbdullatifFacial recognition systems are becoming more prevalent in our daily lives. Based on artificial intelligence, computers play a very important role in the issue of identifying and tracking. This technology is mostly used for security and law enforcement. In view of the COVID-19 pandemic, government directives have been issued to citizens to wear medical masks in crowded institutions and places, … …Journal of Computer Science, Vol. 19, Issue 12 · 28 Oct 2023 · 5,851 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleCrop Disease Detection Using Deep Learning Techniques on ImagesKinjal Vijaybhai Deputy, Kalpdrum Passi, Chakresh Kumar JainAgriculture plays a crucial role in the economic development of many countries and sustains the global population despite facing various challenges like climate change, pollinator decline, and plant diseases. These threats to food security highlight the need for innovative solutions to prevent crop loss. Leveraging smartphone technology for automated image recognition-based disease diagnosis has emerged as a promising approach, thanks … …Journal of Computer Science, Vol. 19, Issue 12 · 25 Oct 2023 · 7,497 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleDataset of Selected Medicinal Plant Species of the Genus Brachylaena: A Comparative Application of Deep Learning Models for Plant Leaf RecognitionAvuya Deyi, Arnaud Nguembang Fadja, Eleonora Deborah Goosen et al.Since several active pharmaceutical ingredients are sourced from medicinal plants, identifying and classifying these plants are generally a valuable and essential task during the drug manufacturing process. For many years, identifying and classifying those plants have been exclusively done by experts in the domain, such as botanists and herbarium curators. Recently, powerful computer vision technologies, using deep learning or deep … …Journal of Computer Science, Vol. 19, Issue 11 · 17 Oct 2023 · 6,219 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleCyber Security Threats and Countermeasures using Machine and Deep Learning Approaches: A SurveyManjula M, Venkatesh, Venugopal K. R.Recent advancements in e-business, e-healthcare, e-governance, and online digital transactions have brought valuable benefits. Unfortunately, it raises severe cyber-attacks. Cyberattacks disrupt normal operations, try to retrieve confidential information and defense secrets, and subvert the nation’s defense systems and Internet-connected devices. Cyber security solutions are required to detect, analyze, defend against threats and protect sensitive data from unauthorized access. This study … …Journal of Computer Science, Vol. 19, Issue 1 · 4 Jan 2023 · 9,370 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleExperimental Evaluation of Coffee Leaf Disease Classification and Recognition Based on Machine Learning and Deep Learning AlgorithmsKacoutchy Jean Ayikpa et al.Coffee plant diseases constitute a significant danger to world coffee production, and the greatest challenge is to detect these diseases as early as possible to save the crop. Traditional methods are most often based on visual observations, often with errors in diagnosing diseases. Machine Learning has become a tool that presents itself as an alternative for automatically identifying plant diseases. … …Journal of Computer Science, Vol. 18, Issue 12 · 10 Dec 2022 · 6,986 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleCombining SMOTE and OVA with Deep Learning and Ensemble Classifiers for Multiclass ImbalancedRattanawadee PanthongThe classification of real-world problems alwaysconsists of imbalanced and multiclass datasets. A dataset having unbalanced andmultiple classes will have an impact on the pattern of the classification modeland the classification accuracy, which will be decreased. Hence,oversampling method keeps the class of dataset balanced and avoids theoverfitting problem. The purposes of the study were to handle multiclassimbalanced datasets and to improve … …Journal of Computer Science, Vol. 18, Issue 8 · 23 Aug 2022 · 6,096 accessesView PDFCite