Results 21 to 30 of about 3,700 (193)
WOT-AE: Weighted Optimal Transport Autoencoder for Patterned Fabric Defect Detection [PDF]
SymmetryPatterned fabrics are characterized by strong periodic and symmetric structures, and defect detection in such materials is essentially the task of identifying local disruptions of global texture symmetry. Conventional low-rank decomposition methods separate defect-free regions as low-rank and defects as sparse components, yet singular value ...
Hui Yang, Lucas Kang, Tianjin Yang
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Quadratic Autoencoder (Q-AE) for Low-Dose CT Denoising
IEEE Transactions on Medical Imaging, 2020 Inspired by complexity and diversity of biological neurons, our group proposed quadratic neurons by replacing the inner product in current artificial neurons with a quadratic operation on input data, thereby enhancing the capability of an individual neuron.
Fenglei Fan +8 more
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The Journal of SupercomputingFeature selection is a fundamental technique for reducing the dimensionality of high-dimensional data by identifying the most relevant features while discarding redundant or irrelevant ones. In unsupervised settings, where labeled data are unavailable and labeling is costly, effective feature selection becomes even more challenging. This paper proposes
Amin Hashemi +3 more
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Credit Card Fraud Detection with Autoencoder and Probabilistic Random Forest
Mathematics, 2021 This paper proposes a method, called autoencoder with probabilistic random forest (AE-PRF), for detecting credit card frauds. The proposed AE-PRF method first utilizes the autoencoder to extract features of low-dimensionality from credit card transaction
Tzu-Hsuan Lin, Jehn-Ruey Jiang
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Linear local tangent space alignment with autoencoder
Complex & Intelligent Systems, 2023 Linear local tangent space alignment (LLTSA) is a classical dimensionality reduction method based on manifold. However, LLTSA and all its variants only consider the one-way mapping from high-dimensional space to low-dimensional space.
Ruisheng Ran, Jinping Wang, Bin Fang
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Proceedings of the ACM Conference on Health, Inference, and Learning, 2020 Systematic review (SR) is an essential process to identify, evaluate, and summarize the findings of all relevant individual studies concerning health-related questions. However, conducting a SR is labor-intensive, as identifying relevant studies is a daunting process that entails multiple researchers screening thousands of articles for relevance.
Eric W, Lee +3 more
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MLP-Mixer-Autoencoder: A Lightweight Ensemble Architecture for Malware Classification
Information, 2023 Malware is becoming an effective support tool not only for professional hackers but also for amateur ones. Due to the support of free malware generators, anyone can easily create various types of malicious code.
Tuan Van Dao, Hiroshi Sato, Masao Kubo
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Split-AE: An Autoencoder-based Disentanglement Framework for 3D Shape-to-shape Feature Transfer
2022 International Joint Conference on Neural Networks (IJCNN), 2022 Sneha Saha +4 more
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Multilayer Fisher extreme learning machine for classification
Complex & Intelligent Systems, 2022 As a special deep learning algorithm, the multilayer extreme learning machine (ML-ELM) has been extensively studied to solve practical problems in recent years.
Jie Lai +4 more
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Anomaly Detection of Metallurgical Energy Data Based on iForest-AE
Applied Sciences, 2022 With the proliferation of the Internet of Things, a large amount of data is generated constantly by industrial systems, corresponding in many cases to critical tasks.
Zhangming Xiong +4 more
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