OM-VST: A video action recognition model based on optimized downsampling module combined with multi-scale feature fusion. by Xiaozhong Geng, Cheng Chen, Ping Yu, Baijin Liu, Weixin Hu, Qipeng Liang, Xintong Zhang

“…This model adds a multi-scale feature fusion module with an optimized downsampling module based on a Video Swin Transformer (VST) to improve the model's ability to perceive and characterize feature information. …”
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Efficient Deep Learning Model Compression for Sensor-Based Vision Systems via Outlier-Aware Quantization by Joonhyuk Yoo, Guenwoo Ban

“…With the rapid growth of sensor technology and computer vision, efficient deep learning models are essential for real-time image feature extraction in resource-constrained environments. …”
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STSG: A Short Text Semantic Graph Model for Similarity Computing Based on Dependency Parsing and Pre-trained Language Models by Hai Liao, Yan Liang, Song Chen, Lingyun Xiang, Zhimin Chang, Yun Xiao

“…Based on this, short text semantic graph (STSG) model based on dependency parsing and pre-trained language models is proposed in this paper. …”
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Domain-Specific Knowledge Graph for Quality Engineering of Continuous Casting: Joint Extraction-Based Construction and Adversarial Training Enhanced Alignment by Xiaojun Wu, Yue She, Xinyi Wang, Hao Lu, Qi Gao

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Increase in efficiency of professionally applied physical training of pupils of 16-17 years old based on application of informational and methodical systems by V.O. Kashuba, N.L. Golovanova

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BERT2DAb: a pre-trained model for antibody representation based on amino acid sequences and 2D-structure by Xiaowei Luo, Fan Tong, Wenbin Zhao, Xiangwen Zheng, Jiangyu Li, Jing Li, Dongsheng Zhao

“…Additionally, existing pre-trained models solely rely on embedding representations using amino acids or k-mers, which do not explicitly take into account the role of secondary structure features. …”
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A Sonar Image Target Detection Method with Low False Alarm Rate Based on Self-Trained YOLO11 Model by Jingqi HAN, Mingxing NAN, Peng ZHANG, Jiajie CHEN, Zhengliang HU

“…This method automatically generated proxy classification tasks based on the sonar image target detection dataset and improved the deep learning detector’s learning of target and background features through pre-training, enhancing the detector’s ability to distinguish between targets and backgrounds and thereby reducing the false alarm rate. …”
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Leveraging Feature Fusion of Image Features and Laser Reflectance for Automated Fish Freshness Classification by Caner Balım, Nevzat Olgun, Mücahit Çalışan

“…Image features were extracted using four pre-trained CNN architectures and fused with laser features to form a unified representation. …”
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Patch-Based Deep-Learning Model With Limited Training Dataset for Liver Tumor Segmentation in Contrast-Enhanced Hepatic Computed Tomography by Yuqiao Yang, Muneyuki Sato, Ze Jin, Kenji Suzuki

“…We applied a multi-scale Hessian ellipsoid enhancer to extract multi-scale features of the liver tumor. We implemented a region-stratified sampling strategy to prevent overfitting in patch-based neural network training. …”
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Educational utility of observational workplace-based assessment modalities in Australian vocational general practice training: a cross-sectional study by Alison Fielding, Benjamin Mundy, Amanda Tapley, Sarah Gani, Rula Ali, Michael Bentley, Rachael Boland, Lina Zbaidi, Elizabeth Holliday, Jean Ball, Mieke van Driel, Linda Klein, Parker Magin

“…In Australian general practice vocational training, external clinical teaching visits (ECTVs) are key observation-based WBAs. …”
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A model for shale gas well production prediction based on improved artificial neural network by LIN Hun, SUN Xinyi, SONG Xixiang, MENG Chun, XIONG Wenxin, HUANG Junhe, LIU Hongbo, LIU Cheng

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Grid Search Based Hyperparameter-Tuned Deep Learning Model for Osteoporosis Diagnosis with Bi-Cubic Interpolation of X-Ray Images by Ruhul Amin, Md.Shamim Reza, Dewan Ahmed Muhtasim, Jungpil Shin, Md. Maniruzzaman, Md.Mahfujul Hasan

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Fine-Grained Fault Diagnosis Method of Rolling Bearing Combining Multisynchrosqueezing Transform and Sparse Feature Coding Based on Dictionary Learning by Guodong Sun, Yuan Gao, Kai Lin, Ye Hu

“…Finally, a linear support vector machine (LSVM) was trained with features of training samples, and the trained LSVM was employed to diagnosis the fault classification of test samples. …”
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Enhancing the FFT-LSTM Time-Series Forecasting Model via a Novel FFT-Based Feature Extraction–Extension Scheme by Kyrylo Yemets, Ivan Izonin, Ivanna Dronyuk

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Vibration-based gearbox fault diagnosis using a multi-scale convolutional neural network with depth-wise feature concatenation. by Van-Trang Nguyen, Quoc Bao Diep

“…This article proposes a novel approach for vibration-based gearbox fault diagnosis using a multi-scale convolutional neural network with depth-wise feature concatenation named MixNet. …”
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3D convolutional neural network based on spatial-spectral feature pictures learning for decoding motor imagery EEG signal by Xiaoguang Li, Xiaoguang Li, Yaqi Chu, Xuejian Wu

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A Chinese Named Entity Recognition Model of Maintenance Records for Power Primary Equipment Based on Progressive Multitype Feature Fusion by Lanfei He, Xuefei Zhang, Zhiwei Li, Peng Xiao, Ziming Wei, Xu Cheng, Shaocheng Qu

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MOMFNet: A Deep Learning Approach for InSAR Phase Filtering Based on Multi-Objective Multi-Kernel Feature Extraction by Xuedong Zhang, Cheng Peng, Ziqi Li, Yaqi Zhang, Yongxuan Liu, Yong Wang

“…To address this issue, this study proposes MOMFNet, a deep learning approach for InSAR phase filtering based on multi-objective multi-kernel feature extraction that leverages multi-objective multi-kernel feature extraction. …”
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FedBFGCN: A Graph Federated Learning Framework Based on Balanced Channel Attention and Cross-Layer Feature Fusion Convolution by Hefei Wang, Ruichun Gu, Jingyu Wang, Xiaolin Zhang, Hui Wei

“…To address this issue, this paper proposes an innovative graph federated learning framework called FedBFGCN (Graph Federated Learning Based on Balanced Channel Attention and Cross-Layer Feature Fusion Convolution) to optimize the embedding and analysis efficiency of graph data. …”
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High-throughput end-to-end aphid honeydew excretion behavior recognition method based on rapid adaptive motion-feature fusion by Zhongqiang Song, Jiahao Shen, Qiaoyi Liu, Wanyue Zhang, Ziqian Ren, Kaiwen Yang, Xinle Li, Jialei Liu, Fengming Yan, Wenqiang Li, Yuqing Xing, Lili Wu

“…Simultaneously, the RT-DETR detection model underwent deep optimization: a spline-based adaptive nonlinear activation function was introduced, and the Kolmogorov-Arnold network was integrated into the deep feature stage of the ResNet50 backbone network to form the RK50 module. …”
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