Marine object detection in forward-looking sonar images via semantic-spatial feature enhancement by Zhen Wang, Zhen Wang, Jianxin Guo, Shanwen Zhang, Nan Xu

“…To address the detection of small-scale marine objects, we develop a context feature extraction module (CFEM), which enhances feature representation for tiny object regions by integrating multi-scale contextual information. …”
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An Information-Extreme Algorithm for Universal Nuclear Feature-Driven Automated Classification of Breast Cancer Cells by Taras Savchenko, Ruslana Lakhtaryna, Anastasiia Denysenko, Anatoliy Dovbysh, Sarah E. Coupland, Roman Moskalenko

“…<b>Conclusions</b>: The proposed information-extreme algorithm utilizing universal cytological features offers a potentially objective and computationally efficient alternative to traditional methods and may mitigate some limitations of deep learning in histopathological analysis. …”
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An Efficient Deep Learning Method for Typhoon Track Prediction Based on Spatiotemporal Similarity Feature Mining by Kaiwen Lixia, Mingyue Lu, Yifei Lu, Hui Liu, Ping Li

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Multiangle Correlation Feature Extraction and Disease Prediction Model Construction for Patients With Post-Stroke Dysarthria by Ting Zhu, Shufei Duan, Huizhi Liang, Fujiang Li, Wei Zhang

“…A total of 154 significant correlation features were extracted for analysis. To mitigate the limitations of subjective clinical scale diagnosis and account for psychological and emotional factors, this study introduced the grey correlation theory and constructed a dysarthria prediction model based on the grey relational analysis-deep belief network (GRA-DBN). …”
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LocaLock: Enhancing Multi-Object Tracking in Satellite Videos via Local Feature Matching by Lingyu Kong, Zhiyuan Yan, Hanru Shi, Ting Zhang, Lei Wang

“…Specifically, LocaLock utilizes an anchor-free detection backbone for efficiency and employs a local cost volume (LCV) module to perform precise feature matching in the local area. This provides valuable object priors to the detection head, enabling the model to “lock” onto objects with greater accuracy and mitigate the instability associated with small object detection. …”
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A fish counting model based on pyramid vision transformer with multi-scale feature enhancement by Jiaming Xin, Yiying Wang, Dashe Li, Zhongliang Xiang

“…Subsequently, a spatial domain multi-scale edge enhancement module is introduced to enhance the detection of fish edge features. This module employs guided filtering and asymmetric convolution to mitigate the effects of noise caused by inadequate and nonuniform illumination. …”
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SFG-Net: A Scattering Feature Guidance Network for Oriented Aircraft Detection in SAR Images by Qingyang Ke, Youming Wu, Wenchao Zhao, Qingbiao Meng, Tian Miao, Xin Gao

“…The former integrates low-level texture and contour features to mitigate detail ambiguity and noise interference, while the latter leverages global context of strong scattering information to generate more discriminative feature representations, guiding the network to focus on critical scattering regions and improving learning of essential features. …”
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Feature fusion ensemble classification approach for epileptic seizure prediction using electroencephalographic bio-signals by Yazeed Alkhrijah, Yazeed Alkhrijah, Shehzad Khalid, Shehzad Khalid, Syed Muhammad Usman, Amina Jameel, Muhammad Zubair, Haya Aldossary, Aamir Anwar, Saad Arif

“…In recent years, multiple researchers have proposed multiple machine learning and deep learning-based methods to predict the onset of seizures using electroencephalogram (EEG) signals before they occur; however, robust preprocessing to mitigate the effect of noise, channel selection to reduce dimensionality, and feature extraction remain challenges in accurate prediction.MethodsThis study proposes a novel method for accurately predicting epileptic seizures. …”
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MRA-YOLOv8: A Network Enhancing Feature Extraction Ability for Photovoltaic Cell Defects by Nannan Wang, Siqi Huang, Xiangpeng Liu, Zhining Wang, Yi Liu, Zhe Gao

“…The coordinate attention network (CANet) is incorporated to mitigate the noise impact of background information on the detection task, and multiple branches are employed to enhance the model’s feature extraction capability. …”
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Influence of Land-Use Type on Black Soil Features in Indonesia Based on Soil Survey Data by Yiyi Sulaeman, Eni Maftuáh, Sukarman Sukarman, Risma Neswati, Nurdin Nurdin, Tony Basuki, Ahmad Suriadi, Ivan Vasenev

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Deep feature batch correction using ComBat for machine learning applications in computational pathology by Pierre Murchan, Pilib Ó Broin, Anne-Marie Baird, Orla Sheils, Stephen P Finn

“…Results: TSS prediction achieved high accuracy (AUROC > 0.95) with all three feature extraction models. ComBat harmonization significantly reduced the AUROC for TSS prediction, with mean AUROCs dropping to approximately 0.5 for most models, indicating successful mitigation of batch effects (e.g., CCL-ResNet50 in TCGA-COAD: Pre-ComBat AUROC = 0.960, Post-ComBat AUROC = 0.506, p < 0.001). …”
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Utilizing Feature Selection Techniques for AI-Driven Tumor Subtype Classification: Enhancing Precision in Cancer Diagnostics by Jihan Wang, Zhengxiang Zhang, Yangyang Wang

“…Artificial intelligence (AI)-powered feature selection offers promising solutions to these issues by automating and refining the feature extraction process. …”
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An effective feature selection approach based on hybrid Grey Wolf Optimizer and Genetic Algorithm for hyperspectral image by Yiqun Shang, Minrui Zheng, Jiayang Li, Xinqi Zheng

“…Abstract Feature selection (FS) is a critical step in hyperspectral image (HSI) classification, essential for reducing data dimensionality while preserving classification accuracy. …”
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A LiDAR SLAM Algorithm Considering Dynamic Extraction of Feature Points in Underground Coal Mine by X. Lin, W. Yao, T. Yan

“…This approach constructs a constraint matrix with rich and robust feature information, enhancing pose estimation accuracy in environments with inadequate feature constraints, mitigating degradation effects, and reducing global cumulative error. …”
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Image small target detection in complex traffic scenes based on Yolov8 multiscale feature fusion by Xuguang Chai, Meizhi Zhao, Jing Li, Junwu Li

“…This innovation facilitates the effective amalgamation of multi-scale features, thereby bolstering the model's proficiency in identifying small targets and enhancing the richness of the contextual information within the output features. …”
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Terminology Alignment based on Multi-level Feature Fusion for Japanese Scientific and Technological Literature Terminology Translation by Qi Fang

“…First, a multi-engine collaborative generation mechanism is designed to produce target pseudo terminology candidates through parallel translations from heterogeneous machine translation systems, effectively expanding the coverage of potential translations while mitigating single-engine bias. Second, a hybrid feature extraction architecture is constructed by integrating Transformer’s multi-head attention with BiLSTM’s sequential modeling capabilities, where positional encoding is deliberately omitted to leverage BiLSTM’s inherent strength in capturing positional relationships, thereby enhancing context-aware feature representation. …”
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Rotation-Invariant Feature Enhancement with Dual-Aspect Loss for Arbitrary-Oriented Object Detection in Remote Sensing by Zhao Hu, Xiangfu Meng, Xinsong Liu, Zhuxiang Sun

“…Specifically, we introduce a rotation-invariant learning (RIL) module, which employs adaptive rotation transformations to enhance shallow feature representations, thereby effectively mitigating interference from complex backgrounds and boosting geometric robustness. …”
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Attention-Guided Sample-Based Feature Enhancement Network for Crowded Pedestrian Detection Using Vision Sensors by Shuyuan Tang, Yiqing Zhou, Jintao Li, Chang Liu, Jinglin Shi

“…Additionally, we integrate these methodologies by aggregating local features between regions of interest (RoI) through the reuse of classification weights, effectively mitigating false positives. …”
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Downhole Coal–Rock Recognition Based on Joint Migration and Enhanced Multidimensional Full-Scale Visual Features by Bin Jiao, Chuanmeng Sun, Sichao Qin, Wenbo Wang, Yu Wang, Zhibo Wu, Yong Li, Dawei Shen

“…Additionally, a multi-scale luminance adjustment module is integrated to merge features across perceptual ranges, mitigating localized brightness anomalies such as overexposure. …”
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SonarNet: Global Feature-Based Hybrid Attention Network for Side-Scan Sonar Image Segmentation by Juan Lei, Huigang Wang, Liming Fan, Qingyue Gu, Shaowei Rong, Huaxia Zhang

“…In addition, an adaptive hybrid attention module is introduced to effectively integrate channel and spatial features, while a global enhancement block fuses multi-scale global and spatial representations from the dual encoders, mitigating information loss throughout the network. …”
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