CR-CLCD: A cross-regional cropland change detection framework with multi-view domain adaptation for high-resolution satellite imagery by Zhendong Sun, Xinyu Wang, Yanfei Zhong

“…Specifically, Pattern Distribution Contrastive (PDC) sub-module achieves feature alignment from the semantic view by imposing contrastive constraints across inter-domain categories. …”
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TIMA-Net: A Lightweight Remote Sensing Image Change Detection Network Based on Temporal Interaction Enhancement and Multi-Scale Aggregation by Zhijun Zhou, Xuejie Zhang, Xiaoliang Luo, Lvchun Wang, Wei Yu, Shufang Xu, Longbao Wang

“…By introducing the timing interaction enhancement module and the progressive decoder based on multi-scale fusion, TIMA-Net improves the accuracy of change detection while ensuring efficient computing performance. …”
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Continuous Sign Language Recognition With Multi-Scale Spatial-Temporal Feature Enhancement by Zhen Wang, Dongyuan Li, Renhe Jiang, Manabu Okumura

“…To solve the above-mentioned issues, in this paper, we propose a spatial-temporal feature-enhanced network, called STNet for CSLR task. …”
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End-to-End Multi-Scale Adaptive Remote Sensing Image Dehazing Network by Xinhua Wang, Botao Yuan, Haoran Dong, Qiankun Hao, Zhuang Li

“…The design of this module can extract important image features at different scales. …”
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A novel intelligent fault diagnosis method for gearbox based on multi-dimensional attention denoising convolution by Wei Liu, Zeqiao Zhang, Zhiwei Ye, Qiyi He

“…The MFRANet employs a multi-scale deep separable convolution module to thoroughly investigate the fundamental characteristics of the original vibration signals in both the time and time-frequency domains. …”
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MFN: Multi-Scale Frequency Feature Fusion Network for Multi-Classification Image Segmentation by Ji Xiao, Li Jianfang, Zhao Peng, Li Xiaochen, Zhang Chengchun, Zheng Junyi, Pang Yonghui, Huang Xiangsheng

“…Recent multi-class segmentation methods often suffer from issues such as boundary ambiguity, loss of detail, and inadequate preservation of contextual information. …”
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A One-Stage HMDV Algorithm Applied in Multitarget Detection in SAR Images by Lei Pang, Weihe Huang, Fengli Zhang, Yinhong Song

“…First, a hybrid feature extraction module is designed to address the computational complexity caused by increased width and depth in convolutional neural networks. …”
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A 3D Dual Encoder Mirror Difference ResU-Net for Multimodal Brain Tumor Segmentation by Qiwei Xing, Zhihua Li, Yongxia Jing, Xiaolin Chen

“…Moreover, a Mirror Difference Feature Fusion (MDFF) module is integrated between the dual encoders and the decoder. …”
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CSCP-YOLO: A Lightweight and Efficient Algorithm for Real-Time Steel Surface Defect Detection by Chenglong Wang, Heng Wang, Yimin Jiang, Lei Yu, Xueting Wang

“…To accelerate defect detection, the SPPF-DW module efficiently fuses multi-scale defect features through optimized computational pathways. …”
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AI-FEED: Prototyping an AI-Powered Platform for the Food Charity Ecosystem by Marcus Sammer, Kijin Seong, Norma Olvera, Susie L. Gronseth, Elizabeth Anderson-Fletcher, Junfeng Jiao, Alison Reese, Ioannis A. Kakadiaris

“…The platform includes a comprehensive mapping and proposal system for community leaders to strategically address local food insecurity issues. AI-FEED’s integrated platform approach allows data sharing across modules, enhancing overall functionality and impact. …”
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RGB-T Object Detection With Failure Scenarios by Qingwang Wang, Yuxuan Sun, Yongke Chi, Tao Shen

“…To further address the issue of redundant information in existing RGB-T object detection models, a redundant information suppression module is introduced, minimizing cross-modal redundant information based on mutual information and contrastive loss. …”
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ADS-YOLO: A Multi-Scale Feature Extraction Remote Sensing Image Object Detection Algorithm Based on Dilated Residuals by Jianying Li, Yajun Chen, Meiqi Niu, Wenhao Cai, Xiaoyang Qiu

“…Lastly, to address the issue of dense targets, we design the Soft-NMS-ShapeIoU module to improve the consistency of bounding boxes and target shapes, while also suppressing adjacent boxes. …”
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USD-YOLO: An Enhanced YOLO Algorithm for Small Object Detection in Unmanned Systems Perception by Hongqiang Deng, Shuzhe Zhang, Xiaodong Wang, Tianxin Han, Yun Ye

“…Second, we introduced the Spatial and Channel Reconstruction Convolution module to reduce redundancy in spatial and channel features while extracting key features of small objects. …”
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A High-Performance and Lightweight Maritime Target Detection Algorithm by Shidan Sun, Zhiping Xu, Xiaochun Cao, Jiachun Zheng, Jiawen Yang, Ni Jin

“…Thus, the ability to handle low visibility and target occlusion issues is enhanced. In the SFPF module, the ghost dynamic convolution combined with low-cost adaptive spatial feature fusion is proposed. …”
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TSFANet: Trans-Mamba Hybrid Network with Semantic Feature Alignment for Remote Sensing Salient Object Detection by Jiayuan Li, Zhen Wang, Nan Xu, Chuanlei Zhang

“…However, the deeper underlying issue lies in how to effectively align and integrate local detail features with global semantic information. …”
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Spatio-temporal transformer and graph convolutional networks based traffic flow prediction by Jin Zhang, Yimin Yang, Xiaoheng Wu, Sen Li

“…In the spatial dimension, the model incorporates a spatial embedding module and a multi-graph convolutional module. The former is designed to learn traffic characteristics of different nodes, and the latter is used to extract spatial correlations effectively from multiple graphs. …”
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A Novel Network for Choroidal Segmentation Based on Enhanced Boundary Information by Wenbo Huang, Chaofan Qu, Yang Yan

“…BENet is constructed on the TransUnet backbone and integrates a boundary enhancement module, leveraging a multi-branch architecture and dilated convolutions to capture features across multiple scales. …”
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Deep nested U-structure network with frequency attention for building semantic segmentation by Khaled Moghalles, Zaid Al-Huda, Dalal AL-Alimi, Yeong Hyeon Gu, Mugahed A. Al-antari

“…We have introduced a novel approach to address these issues: an end-to-end residual U-structure embedded within a U-Net, enhanced by a frequency attention module and a hybrid loss function. …”
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YOLOv8n-RF: A Dynamic Remote Control Finger Recognition Method for Suppressing False Detection by Yawen Wang, Gaofeng Wang, Yining Yao

“…This algorithm utilizes the CRVB-DSConvEMA module in the feature extraction network, adopts the SPPF-DSConvEMA module in the downsampling process, and introduces BiFPN in the Neck layer. …”
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Multi-phase attention network for face super-resolution. by Tao Hu, Yunzhi Chen

“…The above two attention modules form the multi-phase attention mechanism. …”
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