Efficient and Explainable Bearing Condition Monitoring with Decision Tree-Based Feature Learning by Trong-Du Nguyen, Thanh-Hai Nguyen, Danh-Thanh-Binh Do, Thai-Hung Pham, Jin-Wei Liang, Phong-Dien Nguyen

“…Bearings are critical components in rotating machinery, where early fault detection is essential to prevent unexpected failures and reduce maintenance costs. This study presents an efficient and interpretable framework for bearing condition monitoring by combining the Wavelet Packet Transform (WPT)-based feature extraction with a Decision Tree (DT) classifier. …”
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Optimizing Solar Radiation Prediction with ANN and Explainable AI-Based Feature Selection by Ibrahim Al-Shourbaji, Abdalla Alameen

“…Machine learning (ML) models are increasingly recognized for their ability to provide accurate and efficient solutions to SR prediction challenges. This paper presents an Artificial Neural Network (ANN) model optimized using feature selection techniques based on Explainable AI (XAI) methods to enhance SR prediction performance. …”
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MRI-Based Meningioma Firmness Classification Using an Adversarial Feature Learning Approach by Miada Murad, Ameur Touir, Mohamed Maher Ben Ismail

“…Specifically, we present two key contributions: (i) an unsupervised feature extraction approach utilizing the Bidirectional Generative Adversarial Network (BiGAN) and (ii) a depth-wise separable deep learning model were designed to map the relevant MRI features with the predefined meningioma firmness classes. …”
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Detecting Lameness in Dairy Cows Based on Gait Feature Mapping and Attention Mechanisms by Xi Kang, Junjie Liang, Qian Li, Gang Liu

“…Current computer vision approaches often rely on isolated lameness feature quantification, disregarding critical interdependencies among gait parameters. …”
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Graph-contrast ransomware detection (GCRD) with advanced feature selection and deep learning by Suneeta Satpathy, Pratik Kumar Swain

“…GFS utilizes graph neural networks (GNNs) to generate a feature graph, enabling efficient pruning of essential features from portable executable (PE) files. …”
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Blind Recognition of Convolutional Codes Based on the ConvLSTM Temporal Feature Network by Lu Xu, Yixin Ma, Rui Shi, Juanjuan Li, Yijia Zhang

“…The recognition of convolutional codes presents challenges, primarily due to their strong temporal dependencies, varying constraint lengths, and additional contamination from noise. …”
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Hybrid Feature Extraction of Pipeline Microstates Based on Φ-OTDR Sensing System by Yanzhu Hu, Zhen Meng, Xinbo Ai, Han Li, Yu Hu, Huiyang Zhao

“…Meanwhile, their combination features can represent the small differences in pipeline states. …”
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Failure Detection in Sensors via Variational Autoencoders and Image-Based Feature Representation by Luis Miguel Moreno Haro, Adaiton Oliveira-Filho, Bruno Agard, Antoine Tahan

“…This paper presents a novel approach for detecting sensor failures using image-based feature representation and the Convolutional Variational Autoencoder (CVAE) model. …”
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Robust Line Feature Matching via Point–Line Invariants and Geometric Constraints by Chenyang Zhang, Yunfei Xiang, Qiyuan Wang, Shuo Gu, Jianghua Deng, Rongchun Zhang

“…In response, this paper presents a novel line feature matching approach grounded in point–line invariants through spatial invariant relationships. …”
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Altered auditory feature discrimination in a rat model of Fragile X Syndrome. by D Walker Gauthier, Noelle James, Benjamin D Auerbach

“…Together, these findings indicate that cortical hyperexcitability in Fmr1 KO rats may act to preserve signal-to-noise ratios and signal detection threshold at the expense of sound sensitivity and fine feature discrimination, highlighting a potential mechanistic locus for a range of auditory behavioral phenotypes in FXS.…”
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Feature Extraction and Identification of Rheumatoid Nodules Using Advanced Image Processing Techniques by Azmath Mubeen, Uma N. Dulhare

“…Feature importance was assessed using SHAP values. …”
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A Lightweight Tri-Stream Feature Fusion Network for Speech Emotion Recognition by Ronghe Cao, Yunxing Wang, Xiaolong Wu, Shuang Jin, Huiling Niu

“…Existing approaches, focusing on prosodic features or deep representations from pre-trained models, often struggle to capture the full spectrum of emotional cues present in real-world speech. …”
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Feature Constraints Map Generation Models Integrating Generative Adversarial and Diffusion Denoising by Chenxing Sun, Xixi Fan, Xiechun Lu, Laner Zhou, Junli Zhao, Yuxuan Dong, Zhanlong Chen

“…Furthermore, we propose a hybrid attention mechanism that strategically combines channel-wise feature recalibration with coordinate-aware spatial modulation, enabling the enhanced discrimination of geographic features under challenging conditions involving edge ambiguity and environmental noise. …”
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Hybrid Method for Oil Price Prediction Based on Feature Selection and XGBOOST-LSTM by Shucheng Lin, Yue Wang, Haocheng Wei, Xiaoyi Wang, Zhong Wang

“…The intricate interplay of factors influencing oil prices and the pronounced fluctuations present significant obstacles within the realm of oil price forecasting. …”
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LH Gene Cloning, Sequence Feature Analysis and Prokaryotic Expression in Conger myriaster by Yan CHEN, Bao SHI, Chenggang WANG, Wanjun BO, Kewen YAN, Meijun TAO, Xinyu ZHAO, Xiaodong MA

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A New Method for Weak Fault Feature Extraction Based on Improved MED by Junlin Li, Jingsheng Jiang, Xiaohong Fan, Huaqing Wang, Liuyang Song, Wenbin Liu, Jianfeng Yang, Liangchao Chen

“…It should be pointed out that the improper setting of the threshold will cause the target function to be recalculated, and the resulting error will eventually affect the distortion of the target function in the background of strong noise. This paper presents an improved MED based method of fault feature extraction from rolling bearing vibration signals that originate in high noise environments. …”
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A novel edge-feature attention fusion framework for underwater image enhancement by Shuai Shen, Haoyi Wang, Weitao Chen, Pingkang Wang, Qianyong Liang, Xuwen Qin, Xuwen Qin

“…To address these issues, this paper presents the CUG-UIEF algorithm, an underwater image enhancement framework leveraging edge feature attention fusion. …”
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A Deep Learning Method for Automatic Coronal Mass Ejection Feature Identification by P. Yang, H. S. Fu, J. B. Cao, F. Shen

“…As space activities become increasingly frequent and infrastructure more reliant on space-based systems, the rapid and accurate detection and tracking of CMEs is critical. Here, we present a deep learning–based algorithm for automated CME feature extraction, comprising four key stages: image preprocessing, segmentation, tracking, and feature extraction. …”
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A Study on the Effect of Drift Factor on Feature Optimization in Electronic Nose Detection by Minhao Cai, Sai Xu, Xingxing Zhou, Huazhong Lu, Xing Liang

“…Although the effect of drift on the performance of electronic noses is widely recognized, there is still a relative lack of research on how drift affects feature optimization. This study presents a novel idea that drift factors not only affect the direct readings of the sensor but may also have a profound effect on the feature optimization process and hence the compensation of the electronic nose. …”
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Continuous Sign Language Recognition With Multi-Scale Spatial-Temporal Feature Enhancement by Zhen Wang, Dongyuan Li, Renhe Jiang, Manabu Okumura

“…A successful CSLR method relies on the continuous tracking of the presenter’s gestures and facial movements. Existing CSLR methods struggle with fully leveraging fine-grained continuous frame information and often overlook the importance of multi-scale feature integration during decoding. …”
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