Feature Learning with Multi-objective Evolutionary Computation in the generation of Acoustic Features by José Antonio Alves Menezes, Giordano Cabral, Bruno Gomes, Paulo Pereira

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Vibration Fault Diagnosis in Wind Turbines Based on Automated Feature Learning by Angela Meyer

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Drift‐Aware Feature Learning Based on Autoencoder Preprocessing for Soft Sensors by Junming Wang, Jing Shu, Md Masruck Alam, Zhaoli Gao, Zheng Li, Raymond Kai‐Yu Tong

“…In this article, a novel approach is presented for drift‐aware feature learning aimed at calibrating drift biases in soft sensors for long‐term use. …”
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Deep Sparse Auto-Encoder Features Learning for Arabic Text Recognition by Najoua Rahal, Maroua Tounsi, Amir Hussain, Adel M. Alimi

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Cross-Camera Erased Feature Learning for Unsupervised Person Re-Identification by Shaojun Wu, Ling Gao

“…Global and erased features are used together in feature learning which are successful conjunction of BFENet. …”
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Separation of scales and a thermodynamic description of feature learning in some CNNs by Inbar Seroussi, Gadi Naveh, Zohar Ringel

“…Inspired by tools from theoretical physics, the authors propose a simplified description of finite deep neural networks based on two matrix variables per layer and provide analytic predictions for feature learning effects.…”
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Spatio-Temporal Correlation Based Adaptive Feature Learning of Tracking Object by GUO Mingzhe, CAI Zixin, WANG Xinyue, JING Liping, YU Jian

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GAN-Based Image Colorization for Self-Supervised Visual Feature Learning by Sandra Treneska, Eftim Zdravevski, Ivan Miguel Pires, Petre Lameski, Sonja Gievska

“…This is the first time that GANs have been used for self-supervised feature learning through image colorization. Through extensive experiments with the COCO and Pascal datasets, we show an increase of 5% for the classification task and 2.5% for the segmentation task. …”
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Deep Sequential Feature Learning in Clinical Image Classification of Infectious Keratitis by Yesheng Xu, Ming Kong, Wenjia Xie, Runping Duan, Zhengqing Fang, Yuxiao Lin, Qiang Zhu, Siliang Tang, Fei Wu, Yu-Feng Yao

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Proactive Critical Energy Infrastructure Protection via Deep Feature Learning by Konstantina Fotiadou, Terpsichori Helen Velivassaki, Artemis Voulkidis, Dimitrios Skias, Corrado De Santis, Theodore Zahariadis

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SSDFL: Spatial scattering decomposition feature learning for PolSAR image by Chen Yang, Biao Hou, Bo Ren, Xu Liu, Jocelyn Chanussot, Shuang Wang, Licheng Jiao

Subjects: “…Spatial scattering decomposition feature learning (SSDFL)…”
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Joint multi-domain feature learning for image steganalysis based on CNN by Ze Wang, Mingzhi Chen, Yu Yang, Min Lei, Zhexuan Dong

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Multiview Deep Feature Learning Network for SAR Automatic Target Recognition by Jifang Pei, Weibo Huo, Chenwei Wang, Yulin Huang, Yin Zhang, Junjie Wu, Jianyu Yang

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Dense Feature Learning and Compact Cost Aggregation for Deep Stereo Matching by Chenyang Yin, Henghui Zhi, Huibin Li

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Unsupervised Few-Shot Feature Learning via Self-Supervised Training by Zilong Ji, Xiaolong Zou, Tiejun Huang, Si Wu, Si Wu

“…In this paper, we propose an unsupervised feature learning method for few-shot learning. The proposed model consists of two alternate processes, progressive clustering and episodic training. …”
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Perceptual Visual Feature Learning With Applications in Sports Educational Image Understanding by Tengsheng Liu, Minghui Xu

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Medical image segmentation based on deep feature learning and multistage classification by Wang, Xiaohong

“…For more complex and large dermoscopic image data analysis issue, we proposed a novel deep feature learning scheme for skin lesion segmentation. …”
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Deep feature learning for image classification via countering over-fitting by Qing, Yuanyuan

“…This thesis proposes a novel algorithm to alleviate the above mentioned issues by incorporating self-supervised learning into feature learning phase and utilizing reconstruction concept to preserve local geometry. …”
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No-reference hyperspectral image quality assessment via ranking feature learning by Li, Yuyan, Dong, Yubo, Li, Haoyong, Liu, Danhua, Xue, Fang, Gao, Dahua

“…In this paper, we propose a novel no-reference HSI quality assessment metric via ranking feature learning (R-NHSIQA), which calculates the Wasserstein distance between the distribution of the deep features of the reconstructed HSIs and the benchmark distribution. …”
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IFFLC: An Integrated Framework of Feature Learning and Classification for Multiple Diagnosis Codes Assignment by Yuwen Li, Weitong Chen, Deyin Liu, Zhimin Zhang, Shunxiang Wu, Chengyu Liu

Subjects: “…disease-specific feature learning…”
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