Efficient Real-Time Sports Action Pose Estimation via EfficientPose and Temporal Graph Convolution by Yuanzhe Ma, Hui Li, Hongqiao Yan

“…This paper presents a real-time pose estimation framework that integrates EfficientPose and T-GCN (Temporal Graph Convolutional Networks) to address the challenges of dynamic and complex sports scenarios. …”
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Damage Recognition of Road Auxiliary Facilities Based on Deep Convolution Network for Segmentation and Image Region Correction by Yuanshuai Dong, Yanhong Zhang, Yun Hou, Xinlong Tong, Qingquan Wu, Zuofeng Zhou, Yuxuan Cao

“…The highway anti-glare panel missing recognition method based on deep convolution image segmentation and correction uses the vertex distance to quickly determine the external quadrilateral, which is suitable for estimating the shape of the area in a dynamic scene. …”
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BreastCNet: Breast Cancer Detection, Classification, and Localization Convolutional Neural Network With Advanced Optimization Techniques by Hassan Mahichi, Vahid Ghods, Mohammad Karim Sohrabi, Arash Sabbaghi

“…GWO fine-tuned neuron counts in dense layers to enhance feature learning, while PO dynamically adjusted the learning rate to improve convergence. …”
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BCDCNN: breast cancer deep convolutional neural network for breast cancer detection using MRI images by D. E. Martina Jaincy, V. Pattabiraman

“…Here, Breast Cancer Deep Convolutional Neural Network (BCDCNN) is presented for Breast Cancer Detection (BCD) using MRI images. …”
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Advanced holographic convolutional dense networks and Tangent runner optimization for enhanced polycystic ovarian disease classification by Prathibanandhi Jeyashanker, Annie Grace Vimala Georgewilliam Sundaram, Padmakala Sadagopan, Abid Yahya, Ravi Samikannu, Irfan Anjum Badruddin, Sarfaraz Kamangar, Mohamed Ghouse Shukur

“…CoCo-HoloNet is using a layered architecture by integrating convolutional layers, dense blocks, and pooling strategies that leverage capturing and extraction of significant features from the input effectively. …”
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DS-AdaptNet: An Efficient Retinal Vessel Segmentation Framework With Adaptive Enhancement and Depthwise Separable Convolutions by Shuting Chen, Chengxi Hong, Hong Jia

“…These techniques are integrated with an Efficient Depthwise Convolutional Neural Network (ED-CNN) architecture that employs depth-separable convolutions, dramatically reducing computational complexity while maintaining high segmentation accuracy. …”
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High-Resolution Geochemical Data Mapping With Swin Transformer-Convolution-Based Multisource Geoscience Data Fusion by Ye Yuan, Shuguang Zhou, Jianhua Bian, Jinlin Wang, Wei Han, Jining Yan

“…This article proposes a novel multimodal spatial–spectral fusion model with swin transformer and convolutional networks for regression (MSSF-SCR). This model extracts spatial features from multisource geoscience data using a multibranch swin transformer and dynamically adjusts feature weights with the multimodal multihead convolutional attention module. …”
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Bridge Crack Segmentation Algorithm Based on Improved U-Net by Yanhao Fang, Jie LYu, Yonghua Xia, Yingke Wang

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Segmentation of Stone Slab Cracks Based on an Improved YOLOv8 Algorithm by Qitao Tian, Runshu Peng, Fuzeng Wang

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Insulator Defect Detection Algorithm Based on Improved YOLOv11n by Junmei Zhao, Shangxiao Miao, Rui Kang, Longkun Cao, Liping Zhang, Yifeng Ren

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Enhancing security and efficiency in Mobile Ad Hoc Networks using a hybrid deep learning model for flooding attack detection by Pramodh Krishna D., E. Sandhya, Khaja Shareef Sk, Srihari Varma Mantena, Venkata Subbaiah Desanamukula, Ch Koteswararao, Srinivasa Rao Vemula, Maruthi Vemula

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Research on Intelligent Vehicle Tracking Control and Energy Consumption Optimization Based on Dilated Convolutional Model Predictive Control by Lanxin Li, Wenhui Pei, Qi Zhang

“…Next, a dilated convolutional vehicle system model (DCVSM) was designed by combining vehicle dynamics with data-driven modeling techniques. …”
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MVBNSleepNet: A Multi-View Brain Network-Based Convolutional Neural Network for Neonatal Sleep Staging by Ligang Zhou, Minghui Liu, Xia Hu, Laishuan Wang, Yan Xu, Chen Chen, Wei Chen

“…<italic>Methods:</italic> We propose MVBNSleepNet, a multi-view brain network-based convolutional neural network. The framework integrates a multi-view brain network (MVBN) to characterize brain functional connectivity from linear temporal correlation, information-theoretic, and phase-dynamics perspectives, providing comprehensive spatial topological information. …”
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Physics-guided attention-aware convolutional neural networks for identification of magnetic islands in the tearing mode on EAST tokamak by Feifei Long, Yian Zhao, Yunjiao Zhang, Chenguang Wan, Yinan Zhou, Ziwei Qiang, Kangning Yang, Jiuying Li, Tonghui Shi, Bihao Guo, Yang Zhang, Hailing Zhao, Ang Ti, Adi Liu, Chu Zhou, Jinlin Xie, Zixi Liu, Ge Zhuang, the EAST Team

“…An attention mechanism is designed to couple with the convolutional neural networks (CNNs) to improve the capability of feature extraction of signals. …”
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Optical flow estimation based on global cross information and dynamic encoder–dynamic decoder by Haoxin Guo, Yifan Wang, Xiaobo Guo

“…For the decoder, bilinear interpolation and deformable convolution are combined to construct a dynamic anisotropic upsampling module, and dynamic anisotropic upsampling of the input feature maps is realized by adjusting the offsets of the sampling points to enhance the ability to process high-resolution details and complex motion boundaries. …”
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Efficient prediction of aerodynamic forces in rarefied flow using convolutional neural network based multi-process method by Haifeng Huang, Guobiao Cai, Chuanfeng Wei, Baiyi Zhang, Xiang Cui, Yongjia Zhao, Huiyan Weng, Weizong Wang, Lihui Liu, Bijiao He

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A traffic prediction method for missing data scenarios: graph convolutional recurrent ordinary differential equation network by Ming Jiang, Zhiwei Liu, Yan Xu

“…Additionally, GCRNODE employs a data-independent spatiotemporal memory graph convolutional network to capture the dynamic spatial dependencies in missing data scenarios. …”
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A Lightweight and Efficient Plant Disease Detection Method Integrating Knowledge Distillation and Dual-Scale Weighted Convolutions by Xiong Yang, Hao Wang, Qi Zhou, Lei Lu, Lijuan Zhang, Changming Sun, Guilu Wu

“…Subsequently, we developed the DSConv module—a novel convolutional structure employing double-scale weighted convolutions that dynamically adjust to different scale perceptions and optimize attention allocation. …”
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Dilated Convolution and YOLOv8 Feature Extraction Network: An Improved Method for MRI-Based Brain Tumor Detection by Lincy Annet Abraham, Gopinath Palanisamy, Veerapu Goutham

“…Hence this paper, Dilated Convolution and YOLOv8 Feature Extraction Network (DC-YOLOv8FEN) is proposed to improve tumor detection accuracy. …”
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Dual-Branch Attention Convolution Spectral&#x2013;Spatial Feature Extraction Networks for Hyperspectral Image Classification by Genyun Sun, Cheng Jing, Aizhu Zhang, Xiaolin Chen, Hang Fu, Zhaojie Pan, Ji Cheng

“…DACSS encompasses a dual-branch feature extraction module (DFEM) and a spatial&#x2013;spectral feature aggregation module (SSAM). DFEM dynamically extracts different scales features from both spatial and spectral branches by combining attention convolution and spectral&#x2013;spatial attention mechanisms. …”
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