Results 61 to 70 of about 75,818 (178)
A Method for Image Anomaly Detection Based on Distillation and Reconstruction
Sensors, 2023 Image anomaly detection is a trending research topic in computer vision. The objective is to build models using available normal samples to detect various abnormal images without depending on real abnormal samples.
Jiaxiang Luo, Jianzhao Zhang
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A Hybrid Autoencoder Network for Unsupervised Image Clustering
Algorithms, 2019 Image clustering involves the process of mapping an archive image into a cluster such that the set of clusters has the same information. It is an important field of machine learning and computer vision.
Pei-Yin Chen, Jih-Jeng Huang
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Zooming Into Clarity: Image Denoising Through Innovative Autoencoder Architectures
IEEE AccessIn today’s era of increasing data complexity and pervasive noise, robust techniques for data processing, reconstruction, and denoising are crucial.
Khatereh Mohammadi +2 more
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Glaucoma detection in myopic eyes using deep learning autoencoder-based regions of interest
Frontiers in OphthalmologyPurposeTo evaluate the diagnostic accuracy of a deep learning autoencoder-based model utilizing regions of interest (ROI) from optical coherence tomography (OCT) texture enface images for detecting glaucoma in myopic eyes.MethodsThis cross-sectional ...
Christopher Bowd +19 more
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Autoencoding any Data through Kernel Autoencoders
, 2018 This paper investigates a novel algorithmic approach to data representation based on kernel methods. Assuming that the observations lie in a Hilbert space X, the introduced Kernel Autoencoder (KAE) is the composition of mappings from vector-valued Reproducing Kernel Hilbert Spaces (vv-RKHSs) that minimizes the expected reconstruction error.
Laforgue, Pierre +2 more
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IEEE AccessA fault detection method for power conversion circuits using thermal images and a convolutional autoencoder is presented. The autoencoder is trained on thermal images captured from a commercial power module at randomly varied load currents and augmented ...
Noboru Katayama, Rintaro Ishida
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Blind Denoising Autoencoder [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2019 The final version accepted at IEEE Transactions on Neural Networks and Learning ...
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The Astronomical JournalWe present a novel method for anomaly detection in solar system object data in preparation for the Legacy Survey of Space and Time. We train a deep autoencoder for anomaly detection and use the learned latent space to search for other interesting objects.
Brian Rogers +4 more
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The Attention Enhanced Autoencoder for Balise Anomaly Detection in Potting Process
IEEE AccessBalise is a critical trackside component in railway systems, operating in harsh environments where silicone gel potting enhances reliability. However, the potting process is irreversible; defects lead to costly scrap and operational delays.
Ke Ye +5 more
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Cumhuriyet Science Journal, 2017 Adaptive Neuro-Fuzzy Inference Systems (ANFIS)is a hybrid artificial neural network (intelligence) approach that utilizes theability of artificial neural networks to learn, generalize, paralyze and toderive fuzzy logic.
Halil Arslan +4 more
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