Convolutional Autoencoder-Based Flaw Detection for Steel Wire Ropes by Guoyong Zhang, Zhaohui Tang, Jin Zhang, Weihua Gui

“…Comparisons of various methods showed the CDAE-iForest method performed better in discriminative feature learning and flaw isolation with a small amount of flaw training data.…”
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Scale variant vehicle object recognition by CNN module of multi-pooling-PCA process by Yuxiang Guo, Itsuo Kumazawa, Chuyo Kaku

“…The recognition of the same vehicle at different scales requires feature learning with scale invariance. Unlike existing feature vector methods, the normalized PCA eigenvalues calculated from feature maps are used to extract scale-invariant features. …”
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An intelligent system control method based on visual sensor by Haijun Diao, Lina Yin, Bin Liang, Yanyan Chen

“…The experimental results show that our proposed algorithm has improved its overall performance through video feature learning and clustering. It not only pays more attention to video spatial information to enhance the discrimination ability of learned video representations, such as scenes and objects, but also improves the tracking performance of visual sensors under various interference attributes.…”
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Research on Physical Education Teaching in Universities Based on Deep Learning by Wang Tao

“…In this paper, we utilize deep learning methods to perform automatic feature learning from multi-source heterogeneous data, mapping different data into the same hidden space, and obtaining the deep features of the data associated with students and sports. …”
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Visible and Infrared Object Tracking Based on Multimodal Hierarchical Relationship Modeling by Rui Yao, Jiazhu Qiu, Yong Zhou, Zhiwen Shao, Bing Liu, Jiaqi Zhao, Hancheng Zhu

“…Through the incorporation of multiple Transformer encoders and the deployment of self-attention mechanisms, we progressively aggregate and fuse multimodal image features at various stages of image feature learning. Throughout the process of multimodal interaction within the network, we employ a dynamic component feature fusion module at the patch-level to dynamically assess the relevance of visible information within each region of the tracking scene. …”
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Multiview-Learning-Based Generic Palmprint Recognition: A Literature Review by Shuping Zhao, Lunke Fei, Jie Wen

“…Seeking to handle the long-standing interference information in the images, multiview palmprint feature learning has been proposed to enhance the feature expression by exploiting multiple characteristics from diverse views. …”
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Stock Price Movement Prediction Based on a Deep Factorization Machine and the Attention Mechanism by Xiaodong Zhang, Suhui Liu, Xin Zheng

“…In this paper, we constructed a convolutional neural network model based on a deep factorization machine and attention mechanism (FA-CNN) to improve the prediction accuracy of stock price movement via enhanced feature learning. Unlike most previous studies, which focus only on the temporal features of financial time series data, our model also extracts intraday interactions among input features. …”
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DeepDiffusion: Unsupervised Learning of Retrieval-Adapted Representations via Diffusion-Based Ranking on Latent Feature Manifold by Takahiko Furuya, Ryutarou Ohbuchi

“…To obtain such retrieval-adapted features, we introduce the idea of combining diffusion distance on a feature manifold with neural network-based unsupervised feature learning. This idea is realized as a novel algorithm called DeepDiffusion (DD). …”
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SAP-Net: A Simple and Robust 3D Point Cloud Registration Network Based on Local Shape Features by Jinlong Li, Yuntao Li, Jiang Long, Yu Zhang, Xiaorong Gao

“…In addition, the registration method based on the feature learning of PointNet cannot directly or effectively extract local features. …”
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Self-Supervised Cluster-Contrast Distillation Hashing Network for Cross-Modal Retrieval by Haoxuan Sun, Yudong Cao, Guangyuan Liu

“…The method utilizes the clustering results to guide feature learning in an appropriately designed contrast framework. …”
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Incremental Canonical Correlation Analysis by Hongmin Zhao, Dongting Sun, Zhigang Luo

“…Canonical correlation analysis (CCA) is a kind of a simple yet effective multiview feature learning technique. In general, it learns separate subspaces for two views by maximizing their correlations. …”
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SqUNet: An High-Performance Network for Crater Detection With DEM Data by Yaqi Zhao, Hongxia Ye

“…This kind of structure can significantly improve the feature learning ability. Moreover, a skip link is added inside the embedded U-Net structure to retain the feature information of the original map. …”
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Deep Learning Aided Data-Driven Fault Diagnosis of Rotatory Machine: A Comprehensive Review by Shiza Mushtaq, M. M. Manjurul Islam, Muhammad Sohaib

“…A data-driven fault diagnosis framework consists of data acquisition, feature extraction/feature learning, and decision making based on shallow/deep learning algorithms. …”
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Adaptive Machine Learning for Robust Diagnostics and Control of Time-Varying Particle Accelerator Components and Beams by Alexander Scheinker

“…In this work, we propose that the combination of adaptive feedback and machine learning, adaptive machine learning (AML), is a way to combine the global feature learning power of ML methods such as deep neural networks with the robustness of model-independent control. …”
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SAR Remote Sensing Image Ship Detection Method NanoDet Based on Visual Saliency by Fangjian LIU, Yuan LI

“…Finally, the optimized lightweight network model, NanoDet, is used to perform feature learning on the training samples added with the saliency maps, so that the system model can achieve fast and high-precision ship detection effects. …”
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Overlap-Aware Hierarchical Decoder for point cloud registration by Qiang Zhang, Dongqiang Wang, Qianwen Yue

“…Extracting high-quality correspondences is a critical challenge in current feature-learning based point cloud registration methods. …”
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Micrographia-based parkinson’s disease detection using Deep Learning by Navamani THANDAVA MEGANATHAN, Shyamala KRISHNAN

“…Deep Learning (DL) approaches, a subfield of machine learning research represent a useful tool for unsupervised feature learning because they employ a succession of layers, each of which is responsible for extracting different sorts of data. …”
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Visuospatial information foraging describes search behavior in learning latent environmental features by David L. Barack, Akram Bakkour, Daphna Shohamy, C. Daniel Salzman

“…Prior efforts to study latent feature learning often used single decisions, used few features, and failed to distinguish between reward-seeking and information-seeking. …”
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Multi-Task Learning and Temporal-Fusion-Transformer-Based Forecasting of Building Power Consumption by Wenxian Ji, Zeyu Cao, Xiaorun Li

“…The TFT component, which is optimized for feature learning, is integrated to further improve the model’s performance. …”
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Lightweight image matting algorithm based on deep learning by Xujia Qin, Guang Yang, Qin Shao, Hongbo Zheng, Meiyu Zhang

“…Finally, knowledge distillation scheme is designed in part of the encoder‐decoder structure, the corresponding loss function is proposed, and the method of knowledge distillation is used to improve the feature learning ability of the lightweight neural network. …”
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