Arctic tern-optimized weighted feature regression system for predicting bridge scour depth by Jui-Sheng Chou, Asmare Molla

“…This prediction system amalgamates the strengths of hybrid models by uniting a metaheuristic optimization algorithm with weighted features and least squares support vector regression (WFLSSVR). …”
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Efficient Attention Transformer Network With Self-Similarity Feature Enhancement for Hyperspectral Image Classification by Yuyang Wang, Zhenqiu Shu, Zhengtao Yu

“…Recently, transformer has gained widespread application in hyperspectral image classification (HSIC) tasks due to its powerful global modeling ability. However, the inherent high-dimensional property of hyperspectral images (HSIs) leads to a sharp increase in the number of parameters and expensive computational costs. …”
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A Cross-Mamba Interaction Network for UAV-to-Satallite Geolocalization by Lingyun Tian, Qiang Shen, Yang Gao, Simiao Wang, Yunan Liu, Zilong Deng

“…For feature extraction, we design a Siamese Feature Extraction Module (SFEM) based on two basic vision Mamba blocks, enabling the model to capture the correlation between UAV and satellite image features. …”
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Automation of Multi-Class Microscopy Image Classification Based on the Microorganisms Taxonomic Features Extraction by Aleksei Samarin, Alexander Savelev, Aleksei Toropov, Aleksandra Dozortseva, Egor Kotenko, Artem Nazarenko, Alexander Motyko, Galiya Narova, Elena Mikhailova, Valentin Malykh

“…The results (Precision = 0.910, Recall = 0.901, and F1-score = 0.905) confirm the effectiveness of the proposed method for biomedical diagnostic tasks, especially in settings with limited computational resources and a need for feature interpretability. Our approach demonstrates performance comparable to state-of-the-art methods while offering superior efficiency and lightweight design due to its significantly reduced number of parameters.…”
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Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection by Ruo-Fei Xu, Zhen-Jing Liu, Shunan Ouyang, Qin Dong, Wen-Jing Yan, Dong-Wu Xu

“…Model performance was systematically evaluated through discrimination (ROC analysis), calibration (Brier score), and clinical utility analyses (decision curve analysis), with additional validation using random forest and support vector machine algorithms across independent samples. …”
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Bi-temporal Gaussian feature dependency guided change detection in remote sensing images by Yi Xiao, Bin Luo, Jun Liu, Xin Su, Wei Wang

“…It has also achieved state-of-the-art performance on four publicly available datasets – DSIFN-CD, SYSU-CD, LEVIR-CD, and S2Looking, surpassing baseline models by +8.58%, +1.28%, +0.31%, and +3.76%, respectively, in terms of the F1-Score metric.…”
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CFM-UNet: coupling local and global feature extraction networks for medical image segmentation by Ke Niu, Jiacheng Han, Jiuyun Cai

“…Abstract In medical image segmentation, traditional CNN-based models excel at extracting local features but have limitations in capturing global features. …”
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Adaptive Scattering Feature Awareness and Fusion for Limited Training Data SAR Target Recognition by Chenxi Zhao, Daochang Wang, Xianghui Zhang, Yuli Sun, Siqian Zhang, Gangyao Kuang

“…Fortunately, electromagnetic scattering feature (ESF) elegantly and accurately models SAR targets, which describe the intrinsic properties of targets in SAR images. …”
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Dynamic niche technology based hybrid breeding optimization algorithm for multimodal feature selection by Ting Cai, Fan Ma, Zhiwei Ye, Wen Zhou, Mingwei Wang, Qiyi He, Hu Pan, Jun Shen

“…DSMHBO achieved average ACA and HCA values of 93.54% and 95.52%, much higher than the comparison models. It also can identify up to 187 feature subsets on the Lung Cancer dataset, which indicates its ability to locate multiple peaks. …”
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Non-cooperative signal modulation recognition algorithm based on joint feature parameter extraction by Haifei SI, Xingliu HU, Zhen SHI, Shiyong LI

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Interpretable analysis of transformer winding vibration characteristics: SHAP and multi-classification feature optimization by Yongteng Sun, Hongzhong Ma

“…Current research on vibration-based winding looseness struggles to clearly determine the contribution of individual features to the model. This paper proposes using the distribution of the harmonic-to-fundamental frequency ratio as a feature for a 110 kV transformer and introduces the SHapley Additive exPlanations (SHAP) method to analyze feature contributions. …”
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Deep learning and hyperspectral features for seedling stage identification of barnyard grass in paddy field by Siqiao Tan, Qiang Xie, Wenshuai Zhu, Yangjun Deng, Lei Zhu, Xiaoqiao Yu, Zheming Yuan, Zheming Yuan, Yuan Chen, Yuan Chen

“…Notably, this surpasses the capabilities of other models that rely on amalgamations of machine learning algorithms and feature dimensionality reduction methods. …”
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Target Recognition Method Based on Graph Structure Perception of Invariant Features for SAR Images by Jingyi CAO, Yang ZHANG, Ya’nan YOU, Yamin WANG, Feng YANG, Weijia REN, Jun LIU

“…Specifically, to support essential feature extraction in each branch, we design a feature-guided graph feature perception module based on multilevel essential feature modeling. …”
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Reparameterized Feature Aggregation Convolutional Neural Network for Remote Sensing Scene Image Classification by Cuiping Shi, Mengxiang Ding, Liguo Wang

“…First, a RepFormer is constructed to extract multilevel features. Then, a multihead hybrid convolution module is designed to extract spatial features across various scales, enhancing the ability of the model to perceive intricate details and broader contexts simultaneously. …”
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Vehicle detection method based on multi-layer selective feature for UAV aerial images by Yinbao Ma, Yuyu Meng, Jiuyuan Huo

“…In the neck, a multi-layer selective feature fusion pyramid (MS-FPN) is constructed to perform attention-based filtering on high-level semantic features and low-level spatial details, followed by feature enhancement via multiplication and global semantic refinement through residual connections. …”
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Two-Way Feature Extraction Using Sequential and Multimodal Approach for Hateful Meme Classification by Apeksha Aggarwal, Vibhav Sharma, Anshul Trivedi, Mayank Yadav, Chirag Agrawal, Dilbag Singh, Vipul Mishra, Hassène Gritli

“…Both approaches are tested on the validation dataset, and results are found to be promising for both models.…”
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Uncovering shared genetic features between inflammatory bowel disease and systemic lupus erythematosus by Vikram R. Shaw, Jinyoung Byun, Catherine Zhu, Rowland W. Pettit, Jeffrey M. Cohen, Younghun Han, Christopher I. Amos

“…We performed both epidemiological and post-genome wide association study (GWAS) analyses to investigate the shared genetic features between IBD and systemic lupus erythematosus (SLE). …”
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Clinical and histopathological features of lupus nephritis and the risk of long-term kidney outcomes in Indonesia by Ni Made Hustrini, Ni Made Hustrini, Endang Susalit, Monik Ediana Miranda, Meilania Saraswati, Y. K. Onno Teng, Merel van Diepen, Joris I. Rotmans

“…The association between lupus nephritis class and kidney outcomes was analyzed using cumulative incidence plots. A linear mixed-model analysis was performed to assess the association between lupus nephritis class and kidney function decline.ResultsThis study included 268 patients, with a mean age of 28.7 + 8.5 years, and 94.8% were female. …”
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APO-CViT: A Non-Destructive Estrus Detection Method for Breeding Pigs Based on Multimodal Feature Fusion by Jinghan Cai, Wenzheng Liu, Tonghai Liu, Fanzhen Wang, Zhihan Li, Xue Wang, Hua Li

“…By integrating the Vision Transformer and convolutional neural networks, the model extracted and fused features from multimodal data. …”
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Computational intelligence to detect bearing faults using optimal features from motor current signals by G. Geetha, P. Geethanjali

“…The results indicate that machine learning models employing different feature selection techniques exhibit superior performance across different feature dimensions. …”
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