Parallel temporal feature selection based on improved attention mechanism for dynamic gesture recognition by Gongzheng Chen, Zhenghong Dong, Jue Wang, Lurui Xia

“…And the proportion of short-term and long-term features of gestures on channel and spatial axes in each stage of feature learning is quantitatively analyzed, and the final model is determined according to the experimental results. …”
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A Novel Method for Few-Shot Specific Emitter Identification in Non-Cooperative Scenarios by Cunxiang Xie, Limin Zhang, Zhaogen Zhong

“…The feature vectors are then fed to a network model for feature learning. Moreover, a meta-learning algorithm is applied to the network model to adapt to few-shot feature learning. …”
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MFEMDroid: A Novel Malware Detection Framework Using Combined Multitype Features and Ensemble Modeling by Wei Gu, Hongyan Xing, Tianhao Hou

“…To address oversparse datasets and reduce feature learning overhead, we employ an auto-encoder for feature dimensionality reduction. …”
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Hierarchical Attentive Feature Aggregation for Person Re-Identification by Husheng Dong, Ping Lu

“…The hierarchical aggregation and multi-granularity feature learning are integrated into a unified architecture that builds upon OSNet, resulting a resource-economical and effective person re-identification model. …”
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A fuzzy recurrent neural network for driver fatigue detection based on steering-wheel angle sensor data by Zuojin Li, Qing Yang, Shengfu Chen, Wei Zhou, Liukui Chen, Lei Song

“…The study of the robust fatigue feature learning method for the driver’s operational behavior is of great significance for improving the performance of the real-time detection system for driver’s fatigue state. …”
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Müller matrix polarimetry for pancreatic tissue characterization by Paulo Sampaio, Maria Lopez-Antuña, Federico Storni, Jonatan Wicht, Greta Sökeland, Martin Wartenberg, Pablo Márquez-Neila, Daniel Candinas, Brice-Olivier Demory, Aurel Perren, Raphael Sznitman

“…This is, to our knowledge, the first study to use ex-vivo unfixed human pancreatic tissue combined with feature-learning from raw Müller matrix readings for this purpose.…”
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A Rotating Machinery Fault Diagnosis Method Based on Multi-Sensor Fusion and ECA-CNN by Hongxing Wang, Hua Zhu, Huafeng Li

“…Convolutional neural networks (CNNs) have recently shown great potential with excellent automatic feature learning and nonlinear mapping abilities in the field of rotating machinery fault diagnosis. …”
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Lightweight Facial Expression Recognition Based on Class-Rebalancing Fusion Cumulative Learning by Xiangwei Mou, Yongfu Song, Rijun Wang, Yuanbin Tang, Yu Xin

“…A dual-branch network (Regular feature learning and Rebalancing-Cumulative learning Network, RLR-CNet) is proposed, where the RLR-CNet uses the improvement in the lightweight ShuffleNet with two branches (feature learning and class-rebalancing) based on cumulative learning, which improves the efficiency of our model recognition. …”
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Comparative Study of Different Methods in Vibration-Based Terrain Classification for Wheeled Robots with Shock Absorbers by Mingliang Mei, Ji Chang, Yuling Li, Zerui Li, Xiaochuan Li, Wenjun Lv

“…The contributions are two-fold: (1) Several experiments are conducted to exhibit the performance of the existing feature-engineering and feature-learning classification methods; and (2) According to the long short-term memory (LSTM) network, we propose a one-dimensional convolutional LSTM (1DCL)-based VTC method to learn both spatial and temporal characteristics of the dampened vibration signals. …”
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Genetic Programming-Based Feature Construction for System Setting Recognition and Component-Level Prognostics by Francesca Calabrese, Alberto Regattieri, Raffaele Piscitelli, Marco Bortolini, Francesco Gabriele Galizia

“…The literature proposes various methods, including signal processing in the time, frequency, and time–frequency domains, feature selection, and unsupervised feature learning. An emerging task in data science is Feature Construction (FC), which has the advantages of both feature selection and feature learning. …”
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Fault Diagnosis for Rolling Bearing of Combine Harvester Based on Composite-Scale-Variable Dispersion Entropy and Self-Optimization Variational Mode Decomposition Algorithm by Wei Jiang, Yahui Shan, Xiaoming Xue, Jianpeng Ma, Zhong Chen, Nan Zhang

“…Subsequently, a CSvDE-based feature learning model is established to generate the multiscale fault feature space (MsFFS) of frequency components for the improvement of fault feature learning ability. …”
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Atrial Fibrillation Detection Based on a Residual CNN Using BCG Signals by Qiushi Su, Yanqi Huang, Xiaomei Wu, Biyong Zhang, Peilin Lu, Tan Lyu

“…The network has four modules, namely a downsampling convolutional module, a local feature learning module, a global feature learning module, and a classification module, and it extracts local and global features from BCG signals for AF detection. …”
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CMLFormer: CNN and Multiscale Local-Context Transformer Network for Remote Sensing Images Semantic Segmentation by Honglin Wu, Min Zhang, Peng Huang, Wenlong Tang

“…The characteristics of remote sensing images, such as complex ground objects, rich feature details, large intraclass variance and small interclass variance, usually require deep learning semantic segmentation methods to have strong feature learning representation ability. Due to the limitation of convolutional operation, convolutional neural networks (CNNs) are good at capturing local details, but perform poorly at modeling long-range dependencies. …”
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Landslide Extraction Using Mask R-CNN with Background-Enhancement Method by Ruilin Yang, Feng Zhang, Junshi Xia, Chuyi Wu

“…The application of deep learning methods has brought improvements to the accuracy and automation of landslide extractions based on remote sensing images because deep learning techniques have independent feature learning and powerful computing ability. However, in application, the quality of training samples often fails the requirement for training deep networks, causing insufficient feature learning. …”
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A Dual-Attention Deep Discriminative Domain Generalization Model for Hyperspectral Image Classification by Qingjie Zhao, Xin Wang, Binglu Wang, Lei Wang, Wangwang Liu, Shanshan Li

“…In DAD3GM, we mainly design two blocks: dual-attention feature learning (DAFL) and deep discriminative feature learning (DDFL). …”
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A Multi-Scale U-Shaped Convolution Auto-Encoder Based on Pyramid Pooling Module for Object Recognition in Synthetic Aperture Radar Images by Sirui Tian, Yiyu Lin, Wenyun Gao, Hong Zhang, Chao Wang

“…The PPM and the multi-scale feature learning scheme were designed to learn multi-scale features. …”
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Understanding Unsupervised Deep Learning for Text Line Segmentation by Ahmad Droby, Berat Kurar Barakat, Raid Saabni, Reem Alaasam, Boraq Madi, Jihad El-Sana

“…We propose an unsupervised feature learning approach for segmenting text lines of handwritten document images with no labelling effort. …”
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Convolutional transformer-driven robust electrocardiogram signal denoising framework with adaptive parametric ReLU by Jing Wang, Shicheng Pei, Yihang Yang, Huan Wang

“…The proposed APtrans-CNN architecture combines the strengths of transformers in global feature learning and CNNs in local feature learning to address the inadequacy of learning with long sequence time-series features. …”
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Information extraction for maritime security by Li, Wenhan

“…The general process of text classification is text pre-processing, feature learning and classifier construction. This dissertation accomplishes text classification through machine learning and deep learning respectively. …”
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Label propagation via local geometry preserving for deep semi-supervised image recognition by Qing, Yuanyuan, Zeng, Yijie, Huang, Guang-Bin

“…Ablation study confirms synergistic effects from features learned with self-supervision and similarity graph with local geometry preserving. …”
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