4 results for “Denoising Autoencoder”

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Research ArticleOpen accessPhrase in the titleRegularization Method for Solving Denoising and Inpainting Task Using Stacked Sparse Denoising AutoencodersPavel Vyacheslavovich Skribtsov, Sergey Olegovich SurikovThis article offers a regularization method for training stacked sparse denoising autoencoders aimed at designing model description of objects used for image denoising and inpainting. The offered regularization method allows increasing the generalizing ability of model description, which results in greater stability of denoising methods using it with regard to variation of the noise type. This makes the offered method … …American Journal of Applied Sciences, Vol. 13, Issue 1 · 13 Jan 2016 · 7,609 accessesView PDF Cite

Review ArticleOpen accessEvery word in the titleDenoising of Underwater Images with Regulated AutoencodersShreya Priyadarshini Roy, N Maheswari, M Sivagami, Angelin Beulah SIn the domain of underwater image processing, the images obtained in underwater lighting conditions are of very poor in quality and contain distortions due to the scattering of lights and color absorption of images in water. This makes it difficult to analyze these images for scientific, commercial and military purposes. Therefore, there is a need for efficient techniques that can … …Journal of Computer Science, Vol. 20, Issue 6 · 4 Apr 2024 · 5,571 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEW-GAT: Edge-Weighted Graph Attention Framework for Patient-Aware Heart Disease Classification Using Feature-to-Feature Similarity GraphsRamakrishna Reddy Badveli, Nijaguna Gollara Siddappa, Sundeep Kumar KanipakapatnamHeart disease remains an important cause of global death, requiring accurate and clinically interpretable prediction models. However, traditional Machine Learning (ML) methods often fail to capture meaningful dependencies among clinical features and lack robustness across diverse patient populations. To overcome these issues, this research introduces an Edge-Weighted Graph Attention Network (EW-GAT) for patient-aware heart disease classification. The approach first models … …Journal of Computer Science, Vol. 22, Issue 7 · 25 Jul 2026 · 912 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