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10 articles for “Deep Autoencoder”
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Research ArticleOpen accessPhrase in the titlePedestrian Detection in RGB-D Data Using Deep AutoencodersPavel Aleksandrovich Kazantsev, Pavel Vyacheslavovich SkribtsovRecent popularity of RGB-D sensors mostly comes from the fact that RGB-images and depth maps supplement each other in machine vision tasks, such as object detection and recognition. This article addresses a problem of RGB and depth data fusion for pedestrian detection. We propose pedestrian detection algorithm that involves fusion of outputs of 2D- and 3D-detectors based on deep autoencoders. … …American Journal of Applied Sciences, Vol. 12, Issue 11 · 17 Nov 2015 · 6,812 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAutomated Terrain Classification with a Bayesian Hyperparameter Optimized Deep Supervised Autoencoder ModelTiny Du Toit, Hennie Kruger, Annette Van Der MerweTerrain classification according to specific terrain attributes, has become increasingly important in certain decision-making scenarios. Automated robots are often utilized to traverse a specific surface to collect data that can be used in classification models to identify a specific terrain. In this study, a supervised autoencoder model (i.e., an autoencoder combined with a supervised learner such as a multilayer perceptron) … …Journal of Computer Science, Vol. 19, Issue 9 · 31 Aug 2023 · 5,019 accessesView PDFCite
Review ArticleOpen accessIn the keywordsDenoising 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 PDFCite
Research ArticleOpen accessIn the keywordsDehazing Mechanism Using Auto-Encoder with Intensity Attention SystemRajat Tiwari, Bhawna Goyal, Ayush DograIn the modern world, images play a significant medium for communication. Primarily, it is easily transferred and disseminated across various platforms which allows the people to express their ideology and perceptions. Conversely, images can be prone the environmental conditions as the image quality can be affected by the weather circumstances. Particularly, haze images minimize the whole clarity and visibility of … …Journal of Computer Science, Vol. 20, Issue 12 · 25 Nov 2024 · 4,513 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization of Non-Technical Electricity Loss Detection Using Artificial Neural Networks: Case of Cameroon Distribution NetworkLekini Nkodo Claude Bernard, Bell Serge Samuel, Nyemb Nsoga Valjacques et al.Non-Technical Losses (NTL) represent a critical challenge for power utilities, particularly in developing countries. This paper proposes an unsupervised deep learning approach based on an autoencoder to detect abnormal electricity consumption patterns in the Cameroonian distribution network. The model learns normal customer behavior using historical consumption data and identifies anomalies through reconstruction error analysis. Statistical thresholds are applied to classify … …American Journal of Engineering and Applied Sciences, Vol. 19, Issue 1 · 23 Jul 2026 · 1,225 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmploying Hybrid Serial Cascaded Adaptive Network for Anomaly Detection and Prevention in IoT Time Series Data With Optimal Interdomain RoutingKante Satyanarayana, K. VenkateshNowadays, emerging Internet of Things (IoT) in data processing becomes interested research topic and is used for various applications. This varies from big data processing and analytics for accumulating entire sensor data to detect and generate long-term trends. Nevertheless, this results in the requirement for resources like the execution of power, memory, and bandwidth, in which resource-constrained IoT tools suffers … …Journal of Computer Science, Vol. 22, Issue 1 · 21 Feb 2026 · 1,466 accessesView PDFCite
Research ArticleOpen accessIn the abstractBlockchain-Enabled Decisive Red Fox Optimizer-Based Feature Selection With Deep Learning-Based Intrusion Detection SystemC. Ananth, S. Sathiyarani, N. MohananthiniRecently, Intrusion Detection Systems (IDS) using Deep Learning (DL) models become useful in accomplishing network security. The selected features serve as input to the DL model, which is trained on labelled datasets to learn intrinsic patterns distinguishing malicious from normal network behaviour. DL techniques like Convolutional Neural Networks (CNN) are usually utilized. The seamless combination of Public Blockchain (BC) technology … …Journal of Computer Science, Vol. 21, Issue 12 · 20 Jan 2026 · 1,714 accessesView PDFCite
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 PDFCite
Research ArticleOpen accessIn the abstractA Deep Convolutional Neural Wavelet Network for Classification of Medical ImagesRamzi Ben Ali, Ridha Ejbali, Mourad ZaiedThis work present a new solution for medical image classification using the Neural Network (NN) and Wavelet Network (WN) based on the Fast Wavelet Transform (FWT) and the Adaboost algorithm. This method is divided in two stages: The learning stage and the classification stage. The first consists to extract the features using the FWT based on the MultiResolution Analysis (MRA). … …Journal of Computer Science, Vol. 14, Issue 11 · 11 Nov 2018 · 7,620 accessesView PDFCite
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 PDFCite