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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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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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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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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A Trusted and Energy Efficient Approach for Cluster-Based Wireless Sensor Networks by Tianshu Wang, Gongxuan Zhang, Xichen Yang, Ahmadreza Vajdi

“…The approach offers (i) trusted hardware module design; (ii) energy-efficient clustering algorithm; and (iii) network operation. …”
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Multi-Strategy Improvement of Coal Gangue Recognition Method of YOLOv11 by Hongjing Tao, Lei Zhang, Zhipeng Sun, Xinchao Cui, Weixun Yi

“…A detection model, referred to as EBD-YOLO, is proposed based on YOLOv11n. First, the C3k2-EMA module is integrated with the EMA attention mechanism within the C3k2 module of the backbone network, thereby enhancing the model’s feature extraction capabilities. …”
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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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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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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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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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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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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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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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Localization and Pixel-Confidence Network for Surface Defect Segmentation by Yueyou Wang, Zixuan Xu, Li Mei, Ruiqing Guo, Jing Zhang, Tingbo Zhang, Hongqi Liu

“…However, two major challenges persist in specific application scenarios: first, the imbalanced area distribution between defects and the background leads to degraded segmentation performance; second, fine gaps within defects are prone to over-segmentation. To address these issues, this study proposes a two-stage image segmentation network that integrates a Defect Localization Module and a Pixel Confidence Module. …”
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GD-Det: Low-Data Object Detection in Foggy Scenarios for Unmanned Aerial Vehicle Imagery Using Re-Parameterization and Cross-Scale Gather-and-Distribute Mechanisms by Rui Shi, Lili Zhang, Gaoxu Wang, Shutong Jia, Ning Zhang, Chensu Wang

“…(ii) A cross-scale gather-and-distribute pyramid module, which helps to augment the relationship representation of four-scale features via flexible skip fusion and distribution strategies. …”
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Infrared and visible image fusion network based on multistage progressive injection by Kaixuan Chang, Jianhua Huang, Xiyan Sun, Jian Luo, Shitao Bao, Huansheng Huang

“…To effectively leverage the inherent characteristics and complementarity of images, and address the issues of structural blurriness and unclear detailed textures in fused images, we introduce a Dual-channel Shallow Detail Fusion Module (DC-SDFM) and a Deep Feature Fusion Block (DFFB). …”
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AILDP: a research on ship number recognition technology for complex scenarios by Tianjiao Wei, Zhuhua Hu, Yaochi Zhao, Xiyu Fan

“…Secondly, to deal with the issues of blurring and occlusion of ship numbers due to ship movement or bad weather, a module (C2f_IRMB_DRB) is proposed that can capture high-quality features while weighing the computational effort when processing low-quality images. …”
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Hierarchical multi‐modal video summarization with dynamic sampling by Lingjian Yu, Xing Zhao, Liang Xie, Haoran Liang, Ronghua Liang

“…This work proposes a dynamic sampling module that leverages frame‐level motion information to alleviate these issues. …”
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Research on mulberry leaf disease recognition method based on deep learning by Ye Hui, Xiang Donghui, Zeng Songwei

“…The algorithm introduces a deformable convolution module within the Backbone to capture disease details and shapes more flexibly. …”
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