Improvement of the Cross-Scale Multi-Feature Stereo Matching Algorithm by Nan Chen, Dongri Shan, Peng Zhang

“…To address weak-textured regions in large-scale component images and reduce mismatches in stereo matching, we propose a cross-scale multi-feature stereo matching algorithm. In the cost-computation stage, the sum of absolute differences (SAD), census, and modified census cost aggregation are employed as cost-calculation methods. …”
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Speech Analysis as a Tool for Detection and Monitoring of Medical Conditions: A review by Magdalena IGRAS-CYBULSKA, Daria HEMMERLING, Mariusz ZIÓŁKO, Wojciech DATKA, Ewa STOGOWSKA, Michał KUCHARSKI, Rafał RZEPKA, Bartosz ZIÓŁKO

“…A selection of articles was performed to identify studies that assess voice features quantitatively in selected disorders by acoustic and linguistic voice analysis. …”
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Dynamic activation and enhanced image contour features for object detection by Jun Wu, Jiahui Zhu, Xin Tong, Tianliang Zhu, Tianyi Li, Chunzhi Wang

“…This paper proposes a lightweight and efficient object detection model based on YOLOv4, first using the lightweight network GhostNet to extract image features and reduce the number of parameters and computation of the backbone structure; then combining AFmodule and Meta-ACON activation function to enhance the feature extraction capability of the backbone network, which strengthen the mode’s ability to capture image spatial feature information; this paper also designs the RL-PAFPN feature fusion structure is with the Reslayer module to further improve the model’s ability to extract and fuse image features. …”
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LV-FeatEx: Large Viewpoint-Image Feature Extraction by Yukai Wang, Yinghui Wang, Wenzhuo Li, Yanxing Liang, Liangyi Huang, Xiaojuan Ning

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Feature-Separated Lightweight Model for Road Extraction in Wild Environments by Che Shi, Yuefeng Cen, Gang Cen

“…This design enhances prediction performance without significantly increasing parameters, reducing computational demands and making the model more adaptable for large-scale remote sensing tasks. …”
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Co-occurrence feature learning for visual recognition of immature leukocytes by Yi-Ting Hsiao, Si-Wa Chan, Yen-Chieh Ouyang, Ju-Huei Chien

“…Additionally, the model is less demanding in terms of training hardware than attentional mechanism-based models that also have local feature representation. DCONN achieves advanced performance based on small-scale models without requiring much training time. …”
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Leveraging advanced feature extraction for improved kidney biopsy segmentation by Muhammad Wajeeh Us Sima, Chengliang Wang, Muhammad Arshad, Jamshed Ali Shaikh, Salem Alkhalaf, Fahad Alturise

“…While the Segment Anything Model (SAM) excels in natural image segmentation, its direct application to medical imaging underperforms due to (1) insufficient preservation of fine-grained anatomical details, (2) computational inefficiency on gigapixel whole-slide images (WSIs), and (3) poor adaptation to domain-specific features like staining variability and sparse annotations. …”
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Cross-Architecture Vulnerability Detection Combining Semantic and Attribute Feature by LI Kun, LI Bin, ZHU Wenjing, ZHOU Qinglei

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Feature fusion with attributed deepwalk for protein–protein interaction prediction by Mei-Yuan Cao, Suhaila Zainudin, Kauthar Mohd Daud

“…However, current computational methods often rely on single feature types or simple feature concatenation, potentially missing the complex nature of protein interactions. …”
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Boosted-SpringDTW for Comprehensive Feature Extraction of PPG Signals by Jonathan Martinez, Kaan Sel, Bobak J. Mortazavi, Roozbeh Jafari

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Facial Expression Recognition Algorithm Combining Parallel Network Features by MIAO Zhuang, CHENG Wei-yue, LIN Ke-zheng, LI Ao

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Formation of Machine Learning Features Based on the Construction of Tropical Functions by Sergey N. Chukanov, Ilya S. Chukanov

“…To increase the variety of parameters (machine learning features), filtering of object scanning by rows from left to right and scanning by columns from bottom to top are built. …”
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Virtual Reality Video Image Classification Based on Texture Features by Guofang Qin, Guoliang Qin

“…Finally, based on DenseNet, an improved shallow layer dense convolutional neural network (L-DenseNet) is proposed, which can compress network parameters and improve the feature extraction ability of the network. …”
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Lightweight Detection Algorithm for Breast-Mass Features in Ultrasound Images by Taojuan Li, Wen Liu, Mingxian Song, Zheng Gu, Ling Hai

“…First, we introduce an efficient multiscale convolutional (EMSC) module to improve feature extraction from complex backgrounds and enhance multiscale representation. …”
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Features of Generation, Propagation and Application of Special Ultrasonic Impulses in Viscous Liquids by Oleg M. Gradov

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Bearing Fault Prediction Based on Mixed Domain Features and GWO-SVM by Xuan Zhou, Ruiyang Xia, Zhaodong Zhang, Sasa Duan, Mao Cheng, Chengjiang Zhou, Min Mao

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Differentiation of non-ST-segment elevation myocardial infarction from unstable angina using coronary computed tomography angiography: the role of imaging features and pericoronary... by Yang Lu, Qing Wang, Haifeng Liu, Qi Liu, Siqi Wang, Wei Xing

“…BACKGROUND: To ascertain the diagnostic value of radiomic features of pericoronary adipose tissue (PCAT) and other coronary computed tomography angiography (CCTA) parameters for differentiating non-ST-segment-elevation myocardial infarction (NSTEMI) from unstable angina (UA). …”
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Rationalised experiment design for parameter estimation with sensitivity clustering by Harsh Chhajer, Rahul Roy

“…Using two kinetic model systems with distinct dynamical features, we show that PARSEC-based experiments improve the parameter estimation of a complex system. …”
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Facial Feature Extraction Algorithm Based on Improved YOLOv7-Tiny by Yining Yao, Yawen Wang, Changyuan Wang, Yibo Zhang, Tingting Liu, Gaofeng Wang

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Extensive Feature-Inferring Deep Network for Hyperspectral and Multispectral Image Fusion by Abdolraheem Khader, Jingxiang Yang, Sara Abdelwahab Ghorashi, Ali Ahmed, Zeinab Dehghan, Liang Xiao

“…The mathematical solutions class has serious challenges, e.g., computation cost, manually tuning parameters, and the absence of imaging models that laboriously affect the fusion process. …”
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