14 results for “Generative Adversarial Network”

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Review ArticleOpen accessIn the abstractDeepfake Technology: A Comprehensive Review of Trends, Applications, Ethical Concerns, and ChallengesBattula Thirumaleshwari Devi, Rajkumar RajasekaranThe digital age has fundamentally transformed how information is created and disseminated, raising critical concerns about the authenticity and trustworthiness of online content. Recent advances in Artificial Intelligence (AI), particularly deep learning, have given rise to deepfakes: highly realistic synthetic media generated by manipulating or replacing faces, voices, and actions in videos. While deepfake technology offers innovative applications across various … …Journal of Computer Science, Vol. 22, Issue 1 · 17 Feb 2026 · 4,861 accessesView PDF Cite

Research ArticleOpen accessIn the abstractOptimized Fractal Fusion Driven Deep Neural Network: An Efficient Hybrid Methodology for Disease Detection and Classification in Plant LeavesDeepkiran Munjal, Mrinal Pandey, Laxman SinghPlant diseases and pest attacks are among the major issues in agriculture, which have a great impact on crop growth and yield. Early and correct detection of these diseases is vital for effective management and keeping plant health at the desired level. This research proposes a new method for detection and classification of plant diseases, the Optimized Fractional Fusion Deep … …Journal of Computer Science, Vol. 21, Issue 12 · 8 Jan 2026 · 2,223 accessesView PDF Cite

Review ArticleOpen accessIn the abstractUnleashing the Power of Image Denoising: A Comprehensive Review of Classical to Deep Learning MethodsArchana Saini, Ayush DograImage denoising is a vital step in many image processing and computer vision professions that aims to improve picture quality by decreasing noise while maintaining important image information. In this article, a detailed overview is presented of traditional and deep learning based picture denoising approaches. Classical methods, such as linear filtering, transform domain techniques, and patch-based approaches like Non-Local Means … …Journal of Computer Science, Vol. 21, Issue 8 · 8 Oct 2025 · 3,107 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEnhancing the CIC IoT Dataset 2023 for Improved Attack Detection through GANs Augmentation and Federated LearningShahad Alahmari, Noura AleisaThe escalating frequency and sophistication of cyber-attacks on Internet of Things (IoT) devices present a pressing challenge to cybersecurity. With IoT device connections projected to exceed 42 billion by 2025, the vulnerability of these devices to cyber-attacks has never been more evident. This paper investigates the integration of Machine Learning (ML) and data augmentation, specifically Generative Adversarial Networks (GAN) and … …Journal of Computer Science, Vol. 21, Issue 7 · 18 Jul 2025 · 9,111 accessesView PDF Cite