Unsupervised Multi-Level Feature Extraction for Improvement of Hyperspectral Classification von Qiaoqiao Sun, Xuefeng Liu, Salah Bourennane

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RANet: Relationship Attention for Hyperspectral Anomaly Detection von Yingzhao Shao, Yunsong Li, Li Li, Yuanle Wang, Yuchen Yang, Yueli Ding, Mingming Zhang, Yang Liu, Xiangqiang Gao

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A Hybrid Autoencoder Network for Unsupervised Image Clustering von Pei-Yin Chen, Jih-Jeng Huang

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EBARec-BS: Effective Band Attention Reconstruction Network for Hyperspectral Imagery Band Selection von Yufei Liu, Xiaorun Li, Ziqiang Hua, Liaoying Zhao

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River Channel Microgeomorphic Feature Extraction and Potential Sandstorm Source Identification Method Based on a Convolutional Autoencoder Model von Kecong Wu, Lirong Chen, Yalige Bai, Xinhang Wang, Danzeng Pingcuo, Zhongpeng Han, Chengshan Wang

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Multi-perspective Learning Based on Transformer for Stock Price Trend von Xiliang Li, Shuoru Chen, Xiaoyan Qiao, Mingli Zhang, Caiming Zhang, Feng Zhao

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Ultrasonic Weld Quality Inspection Involving Strength Prediction and Defect Detection in Data-Constrained Training Environments von Reenu Mohandas, Patrick Mongan, Martin Hayes

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Multi-Aspect Convolutional-Transformer Network for SAR Automatic Target Recognition von Siyuan Li, Zongxu Pan, Yuxin Hu

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Prediction of Contact Fatigue Performance Degradation Trends Based on Multi-Domain Features and Temporal Convolutional Networks von Yu Liu, Yuanbo Liu, Yan Yang

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A study on hybrid-architecture deep learning model for predicting pressure distribution in 2D airfoils von Jaehyun Yoon, Jaehyeok Doh

Schlagworte: “… Convolutional autoencoder (CAE) …”
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Canopy Averaged Chlorophyll Content Prediction of Pear Trees Using Convolutional Autoencoder on Hyperspectral Data von Subir Paul, Vinayaraj Poliyapram, Nevrez Imamoglu, Kuniaki Uto, Ryosuke Nakamura, D. Nagesh Kumar

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Seismic Data Compression Using Deep Learning von Emad B. Helal, Omar M. Saad, Ali G. Hafez, Yangkang Chen, Gamal M. Dousoky

Schlagworte: “… Convolutional autoencoders (CAE) …”
Volltext

Defect Detection for Enhanced Traceability in Naval Construction von Paula Arcano-Bea, Manuel Rubiños, Agustín García-Fischer, Francisco Zayas-Gato, José Luis Calvo-Rolle, Esteban Jove

Schlagworte: “… convolutional autoencoders (CAEs) …”
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