MDA-MIM: a radar echo map prediction model integrating multi-scale feature fusion and dual attention mechanism by HU Qiang, GAO Yating, YIN Binli, QU Lianen

“…Multi-scale feature fusion and a dual attention mechanism were incorporated in MDA-MIM. Dilated convolution was used to extract and integrate multi-scale features. …”
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MDFusion: Multi-Dimension Semantic–Spatial Feature Fusion for LiDAR–Camera 3D Object Detection by Renzhong Qiao, Hao Yuan, Zhenbo Guan, Wenbo Zhang

“…Additionally, LiDAR BEV features are fused with downsampled image features in 2D space via concatenation and spatially adaptive dilated convolution. The mechanism dynamically adjusts to the spatial characteristics of the data, ensuring robust feature integration. …”
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DSF-YOLO for robust multiscale traffic sign detection under adverse weather conditions by Jun Li, QinWen Deng, WenXin Gao, Bing Yang, Lan Jia, Ju Zhou, HaiBo Pu

“…Additionally, the model integrates a dynamic snake convolution operator along with Wise-IoU, enabling it to capture fine small-scale feature information while mitigating the impact of low-quality instances. …”
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Improved Face Image Super-Resolution Model Based on Generative Adversarial Network by Qingyu Liu, Yeguo Sun, Lei Chen, Lei Liu

“…First, a Multi-scale Hybrid Attention Residual Block (MHARB) is designed, which dynamically enhances feature representation in critical face regions through dual-branch convolution and channel-spatial attention. …”
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A small object detection model in aerial images based on CPDD-YOLOv8 by Jingyang Wang, Jiayao Gao, Bo Zhang

“…Thirdly, a new DSC2f structure is proposed, which uses Dynamic Snake Convolution (DSConv) to take the place of the first standard Conv of Bottleneck in the C2f structure, so that the model can adapt to different inputs more effectively. …”
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Semi-supervised machine learning for primary user emulation attack detection and prevention through core-based analytics for cognitive radio networks by Sundar Srinivasan, KB Shivakumar, Muazzam Mohammad

“…In this paper novel method is proposed to leverage unique methodology which can efficiently handle during various dynamic changes includes varying bandwidth, signature changes etc… performing learning and classification at edge nodes followed by core nodes using deep learning convolution network. …”
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Load Reconstruction Technique Using D-Optimal Design and Markov Parameters by Deepak K. Gupta, Anoop K. Dhingra

“…This paper develops a technique for identifying dynamic loads acting on a structure based on impulse response of the structure, also referred to as the system Markov parameters, and structure response measured at optimally placed sensors on the structure. …”
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A Multi-Scale Adaptive Fusion Network: End-to-End Interpretable Small-Sample Classifier for Motor Imagery EEG by Qiulei Han, Yan Sun, Ze Song, Hongbiao Ye, Tingwei Chen, Jian Zhao

“…Existing studies often struggle with feature extraction, dynamic feature selection, and temporal modeling, failing to capture critical EEG patterns effectively. …”
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CGLCS-Net: Addressing Multi-Temporal and Multi-Angle Challenges in Remote Sensing Change Detection by Ke Liu, Hang Xue, Caiyi Huang, Jiaqi Huo, Guoxuan Chen

“…We propose the Context-Aware Global-Local Subspace Attention Change Detection Network (CGLCS-Net) to resolve these issues and introduce the Global-Local Context-Aware Selector (GLCAS) and the Subspace-based Self-Attention Fusion (SSAF) module. GLCAS dynamically selects receptive fields at different feature extraction stages through a joint pooling attention mechanism and depthwise separable convolution, enhancing global context and local feature extraction capabilities and improving feature representation for multi-scale and irregular change regions. …”
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EDT-Net: A Lightweight Tunnel Water Leakage Detection Network Based on LiDAR Point Clouds Intensity Images by Zhenyu Liu, Xianjun Gao, Yuanwei Yang, Lei Xu, Shaoning Wang, Ningsheng Chen, Zhiwei Wang, Yuan Kou

“…Finally, we employed a twin attention-guided dynamic detection-head to improve detection performance. …”
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Intelligent deep learning architecture for precision vegetable disease detection advancing agricultural new quality productive forces by Jun Liu, Xuewei Wang, Qian Chen, Peng Yan, Dugang Guo

“…The Adaptive Detail Enhancement Convolution (ADEConv) module employs dynamic parameter adjustment to preserve fine-grained features while maintaining computational efficiency. …”
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Spectrum sensing based on adversarial transfer learning by Jiawu Miao, Yuebo Li, Xiaojun Jing, Fangpei Zhang, Junsheng Mu

“…However, the model robustness of the DL based scheme is limited by reason of the dynamic radio environment, leading to the floating of sensing performance. …”
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A Convolve-And-MErge Approach for Exact Computations on High-Performance Reconfigurable Computers by Esam El-Araby, Ivan Gonzalez, Sergio Lopez-Buedo, Tarek El-Ghazawi

“…A Convolve-And-MErge approach is proposed, that implements virtual convolution schedules derived from the formal representation of the arbitrary-precision multiplication problem. …”
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MSM-TDE: multi-scale semantics mining and tiny details enhancement network for retinal vessel segmentation by Hongbin Zhang, Jin Zhang, Xuan Zhong, Ya Feng, Guangli Li, Xiong Li, Jingqin Lv, Donghong Ji

“…Additionally, an auxiliary vessel detail enhancement branch using dynamic snake convolution is built to enhance the tiny vessel details. …”
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Multimission Observations of Relativistic Electrons and High-speed Jets Linked to Shock-generated Transients by Savvas Raptis, Martin Lindberg, Terry Z. Liu, Drew L. Turner, Ahmad Lalti, Yufei Zhou, Primož Kajdič, Athanasios Kouloumvakos, David G. Sibeck, Laura Vuorinen, Adam Michael, Mykhaylo Shumko, Adnane Osmane, Eva Krämer, Lucile Turc, Tomas Karlsson, Christos Katsavrias, Lynn B. Wilson III, Hadi Madanian, Xóchitl Blanco-Cano, Ian J. Cohen, C. Philippe Escoubet

“…Additionally, high-speed jets form at the compressive edges of HFAs, exhibiting a significant increase in dynamic pressure and potentially contributing to further localized compression. …”
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Lightweight Human Behavior Recognition Method for Visual Communication AGV Based on CNN-LSTM by Shuhua Zhao, Jianxin Zhu, Jiang Lu, Zhibo Ju, Dong Wu

“…The S-MobileNet is proposed for human behavior recognition. Firstly, the 3D convolution to extract features is used to build a time series model to learn the long-term dependence of human behavior characteristics on time series. …”
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A Lightweight Multi-Frequency Feature Fusion Network with Efficient Attention for Breast Tumor Classification in Pathology Images by Hailong Chen, Qingqing Song, Guantong Chen

“…The network’s ability to extract irregular tumor characteristics is further reinforced by dynamic adaptive deformable convolution (DADC). The introduction of the token-based Region Focus Module (TRFM) reduces interference from irrelevant background information. …”
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Estimating Bandwidth and Analyzing Worst-Case Delay Bounds Using Network Calculus by Md Amirul Islam, Giovanni Stea

“…Our approach models available bandwidth as a service curve and employs min-plus algebra-specifically, convolution and deconvolution operations-to derive end-to-end predictions from individual link characteristics. …”
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The 3D tooth model segmentation method based on GAC+PointMLP network by Jianjun Chen, Liyuan Zheng, Huilai Zou, Jiafa Mao, Weiguo Sheng

“…By incorporating the GAC Layer into PointMLP, the model can focus on key local regions in the 3D tooth model and dynamically adjust the attention applied to these areas. …”
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Improvement in Pavement Defect Scenarios Using an Improved YOLOv10 with ECA Attention, RefConv and WIoU by Xiaolin Zhang, Lei Lu, Hanyun Luo, Lei Wang

“…The RefConv dual-branch structure achieves feature complementarity between local details and global context (mAP increased by 2.1%), the ECA mechanism models channel relationships using 1D convolution (small-object recall rate increased by 27%), and the WIoU loss optimizes difficult sample regression through a dynamic weighting mechanism (location accuracy improved by 37%). …”
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