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128 results for “Machine Learning and Deep Learning”

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Research ArticleOpen accessIn the keywordsTomato Leaf Disease Detection by Hybrid Ai and Ml TechnologyP. Loganathan, M. John Britto, Vinston RajaDiseases that affect plants contribute to productivity decline, but they can be managed with ongoing monitoring. It is time-consuming and prone to error to track plant diseases manually. Early disease detection using Artificial Intelligence (AI) and machine vision can lessen negative impacts while also overcoming some of the limitations of continuous human monitoring. Therefore, this study uses both Deep Learning … …Journal of Computer Science, Vol. 21, Issue 12 · 12 Feb 2026 · 1,881 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPrivacy-Preserving Deep Federated Learning on the Edge Using Homomorphic Encryption and Secure Multiparty ComputationNoman Aasif Gudur, Mohamed El-Dosuky, Sherif KamelThe increasing volume of consumer data necessitates reliable edge devices for personalized user experiences. Federated Learning (FL) offers a state-of-the-art approach to decentralized machine learning by leveraging data distributed across multiple client devices. However, user data privacy remains vulnerable to corruption through feature heterogeneity and malicious attacks. While several privacy-preserving techniques have been previously implemented, they suffer from implementation constraints … …Journal of Computer Science, Vol. 21, Issue 11 · 21 Dec 2025 · 4,381 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Integrated Framework to Predict the Strength of New SMILE Using Graph Attention NetworkSandhi Kranthi Reddy, S. V. G. ReddyMachine Learning (ML) and Deep Learning (DL) have significantly advanced various fields, including healthcare, finance, autonomous systems, and scientific research. In healthcare, these technologies have been widely applied to disease prediction, such as cancer and diabetes. However, the challenge of drug resistance persists, creating a need for more effective drugs. Developing new drugs is a complex, expensive, and time-intensive process, … …Journal of Computer Science, Vol. 21, Issue 10 · 25 Nov 2025 · 2,157 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHybrid Deep Learning Models for Text Classification: Performance Evaluation of TriDistilBERT and BiGRU ArchitecturesAmira Samy TalaatText can be a valuable source of information, but its unstructured nature makes analysis challenging and time-consuming. Machine Learning (ML) algorithms can efficiently analyze and structure text, enabling organizations to automate processes and uncover insights that support better decision-making. This study focuses on applying ML to a classification problem using two datasets. Four deep learning models are introduced, combining Bi … …Journal of Computer Science, Vol. 21, Issue 9 · 10 Oct 2025 · 2,792 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSecuring IoT Networks: Multi-Attack Detection of RPL Routing Threats Using Deep LearningAyoub Krari, Abdelmajid Hajami, Ayoub Toubi, Marouane Ait SaidThe growing frequency of cyber threats in Internet of Things (IoT) networks, including attacks on RPL routing, requires the creation of strong detection systems to safeguard network integrity and provide dependable communication. This study is driven by the pressing necessity to tackle the security weaknesses in IoT networks, where threats such as black holes, version number alteration, DIS flooding, and … …Journal of Computer Science, Vol. 21, Issue 4 · 6 Mar 2025 · 5,397 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEnhancing Telecommunication Network Management with Autonomous Optimization Agents and Machine LearningDanny Adil Sibarani, Evaristus Didik MadyatmadjaThis study explores the integration of Machine Learning (ML) and Autonomous Optimization Agents (AOAs) in the management and optimization of Radio Access Networks (RAN). The research addresses the growing challenges posed by the need for skilled network experts capable of managing and analyzing large-scale network data, including Key Performance Indicators (KPIs) and thousands of network configuration parameters. To overcome these … …Journal of Computer Science, Vol. 21, Issue 2 · 4 Mar 2025 · 7,041 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Deep Ensemble Framework for DDoS Attack Recognition and Mitigation in Cloud SDN EnvironmentS. Annie Christila, R. SivakumarMuch research has been done in the recent past on the absolute shift of Internet infrastructure in order to make it more significantly programmable, configurable and make it more conveniently feasible. Software Defined Networking (SDN) forms the basis for this absolute shift in Internet infrastructure. When you look at the benefits of an SDN-based cloud environment they are monumental. Namely, … …Journal of Computer Science, Vol. 20, Issue 10 · 5 Aug 2024 · 5,337 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPhishing Website Detection Using Improved Multilayered Convolutional Neural NetworksHadia Bibi, Syed Rehan Shah, Mirza Murad Baig et al.The internet has become an essential part of many fields: Communication, entertainment, commerce, industrial production, agriculture, etc. Unfortunately, online users are vulnerable to various attacks; this could lead to financial damages and loss of personal information. Phishing is seen as an internet threat and a cybercrime where anyone can capture personal information and data by posing as a reliable source. … …Journal of Computer Science, Vol. 20, Issue 9 · 6 Jul 2024 · 6,578 accessesView PDFCite
Research ArticleOpen accessIn the keywordsImproving 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 accessIn the keywordsSecuring 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