Unsupervised Domain Adaptation via Weighted Sequential Discriminative Feature Learning for Sentiment Analysis by Haidi Badr, Nayer Wanas, Magda Fayek

“…This potentially leads to instability during shared-feature learning. To tackle this issue, WS-UDA employs a two-stage transfer process concurrently, significantly enhancing model stability and adaptability. …”
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Multi-Labeled Recognition of Distribution System Conditions by a Waveform Feature Learning Model by Sang-Keun Moon, Jin-O Kim, Charles Kim

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Feature Learning for Stock Price Prediction Shows a Significant Role of Analyst Rating by Jaideep Singh, Matloob Khushi

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Cable Incipient Fault Identification Method Using Power Disturbance Waveform Feature Learning by Hong Lu, Wen-Hai Zhang, Ying Wang, Xian-Yong Xiao

“…This paper fully considers the randomness and uncertainty of CIF waveforms, and proposes a CIF identification method using power disturbance waveform feature learning. Firstly, the shallow features are extracted to characterize the transient components of different disturbance current waveforms, by conducting a stationary wavelet transform. …”
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Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning by Chuan Li, René-Vinicio Sánchez, Grover Zurita, Mariela Cerrada, Diego Cabrera

“…To tackle this problem, a model for deep statistical feature learning from vibration measurements of rotating machinery is presented in this paper. …”
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Multi-branch feature learning based speech emotion recognition using SCAR-NET by Keji Mao, Yuxiang Wang, Ligang Ren, Jinhong Zhang, Jiefan Qiu, Guanglin Dai

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Accurate Instance Segmentation for Remote Sensing Images via Adaptive and Dynamic Feature Learning by Feng Yang, Xiangyue Yuan, Jie Ran, Wenqiang Shu, Yue Zhao, Anyong Qin, Chenqiang Gao

“…These three modules enable a better feature learning of the instance segmentation network. …”
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A conditional random field based feature learning framework for battery capacity prediction by Hai-Kun Wang, Yang Zhang, Mohong Huang

“…The model uses LSTM to extract temporal features from the data and CRF to build a transfer matrix to enhance temporal feature learning for long serialization prediction of lithium battery feature sequence data. …”
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Predicting Cardiovascular Rehabilitation of Patients with Coronary Artery Disease Using Transfer Feature Learning by Romina Torres, Christopher Zurita, Diego Mellado, Orietta Nicolis, Carolina Saavedra, Marcelo Tuesta, Matías Salinas, Ayleen Bertini, Oneglio Pedemonte, Marvin Querales, Rodrigo Salas

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Robust detection of marine life with label-free image feature learning and probability calibration by Tobias Schanz, Klas Ove Möller, Saskia Rühl, David S Greenberg

“…To overcome these obstacles for automated underwater imaging, we combine and test recent developments in deep classifier networks and self-supervised feature learning. We use unlabeled images for pretraining deep neural networks to extract task-relevant image features, allowing learning algorithms to cope with scarcity in expert labels, and carefully evaluate performance in subsequent label-based tasks. …”
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MSFL: Explainable Multitask-Based Shared Feature Learning for Multilingual Speech Emotion Recognition by Yiping Ma, Wei Wang

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Parameter sharing and multi-granularity feature learning for cross-modality person re-identification by Sixian Chan, Feng Du, Tinglong Tang, Guodao Zhang, Xiaoliang Jiang, Qiu Guan

“…For the part-level feature learning, the hetero-center triplet loss is adopted to alleviate the strict constraints of triplet loss. …”
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An Adaptive Feature Learning Model for Sequential Radar High Resolution Range Profile Recognition by Xuan Peng, Xunzhang Gao, Yifan Zhang, Xiang Li

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XGBoost-Based Feature Learning Method for Mining COVID-19 Novel Diagnostic Markers by Xianbin Song, Jiangang Zhu, Xiaoli Tan, Wenlong Yu, Qianqian Wang, Dongfeng Shen, Wenyu Chen

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Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning by Dan Stowell, Mark D. Plumbley

“…In this work we introduce a technique for feature learning from large volumes of bird sound recordings, inspired by techniques that have proven useful in other domains. …”
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Visual Feature Learning on Video Object and Human Action Detection: A Systematic Review by Dengshan Li, Rujing Wang, Peng Chen, Chengjun Xie, Qiong Zhou, Xiufang Jia

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An overview on data representation learning: From traditional feature learning to recent deep learning by Guoqiang Zhong, Li-Na Wang, Xiao Ling, Junyu Dong

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Robust and accurate pulmonary nodule detection with self-supervised feature learning on domain adaptation by Jingya Liu, Liangliang Cao, Oguz Akin, Yingli Tian

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One class based feature learning approach for defect detection using deep autoencoders by Abdul Mujeeb, Dai, Wenting, Erdt, Marius, Sourin, Alexei

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Unsupervised feature learning with sparse Bayesian auto-encoding based extreme learning machine by Zhang, Guanghao, Cui, Dongshun, Mao, Shangbo, Huang, Guang-Bin

“…Extreme learning machine (ELM) is a popular method in machine learning with extremely few parameters, fast learning speed and model efficiency. Unsupervised feature learning based ELM receives rising research focus. …”
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