Results 11 to 20 of about 113,519 (298)
Bearing Vibration Abnormal Detection Based on Improved Autoencoder Network [PDF]
Jisuanji kexue yu tansuo, 2022 In recent years, autoencoders and neural network technologies have been widely studied and applied to abnormal data detection problems of industrial data such as bearing vibration, but there are still problems such as large training data, network ...
LI Beibei, PENG Li
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Complex-valued autoencoders [PDF]
Neural Networks, 2012 Autoencoders are unsupervised machine learning circuits whose learning goal is to minimize a distortion measure between inputs and outputs. Linear autoencoders can be defined over any field and only real-valued linear autoencoder have been studied so far.
Baldi, Pierre, Lu, Zhiqin
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Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2023 This paper presents a new hybrid algorithm using multiple Support Vector Machines models with convolutional autoencoder to Electrical Impedance Tomography, and Ultrasound Computed Tomography image reconstruction.
Łukasz Maciura +3 more
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Extended Autoencoder for Novelty Detection with Reconstruction along Projection Pathway
Applied Sciences, 2020 Recently, novelty detection with reconstruction along projection pathway (RaPP) has made progress toward leveraging hidden activation values. RaPP compares the input and its autoencoder reconstruction in hidden spaces to detect novelty samples ...
Seung Yeop Shin, Han-joon Kim
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An Integrative Remote Sensing Application of Stacked Autoencoder for Atmospheric Correction and Cyanobacteria Estimation Using Hyperspectral Imagery [PDF]
, 2020 Hyperspectral image sensing can be used to effectively detect the distribution of harmful cyanobacteria. To accomplish this, physical- and/or model-based simulations have been conducted to perform an atmospheric correction (AC) and an estimation of ...
Baek, Sangsoo +10 more
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Review on autoencoder and its application
Tongxin xuebao, 2021 As a typical deep unsupervised learning model, autoencoder can automatically learn effective abstract features from unlabeled samples.In recent years, autoencoder has been widely used in target recognition, intrusion detection, fault diagnosis and many ...
Jie LAI +4 more
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Energy Reports, 2021 Anomaly detection for hydropower turbine unit is a requirement for the safety of hydropower system. An unsupervised anomaly detection method employing variational modal decomposition (VMD) and deep autoencoder is proposed.
Hongteng Wang +3 more
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Unsupervised Outlier Detection via Transformation Invariant Autoencoder
IEEE Access, 2021 Autoencoder based methods are the majority of deep unsupervised outlier detection methods. However, these methods perform not well on complex image datasets and suffer from the noise introduced by outliers, especially when the outlier ratio is high.
Zhen Cheng +4 more
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Identifikasi Penulis Berdasarkan Pola Tulisan Tangan Menggunakan Convolutional Autoencoder dan KNN
Journal of Electrical Engineering and Computer, 2021 Identifikasi tulisan tangan dilakukan dengan beberapa tahapan, yaitu Akuisisi Citra dengan memanfaatkan mesin scanner dengan kualitas gambar 300dpi, Segmentasi dilakukan dengan metode threshold dan seleksi kontour dari gambar, penggabungan gambar hasil ...
Muhammad Turmudzi, Endang Setyati
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Machine Learning and Knowledge Extraction, 2023 The proliferation of novel attacks and growing amounts of data has caused practitioners in the field of network intrusion detection to constantly work towards keeping up with this evolving adversarial landscape.
Brian Lewandowski, Randy Paffenroth
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