Neural Network for Underwater Fish Image Segmentation Using an Enhanced Feature Pyramid Convolutional Architecture by Guang Yang, Junyi Yang, Wenyao Fan, Donghe Yang

“…However, typical underwater fish images often suffer from issues such as color distortion, low contrast, and blurriness, primarily due to the complex and dynamic nature of the marine environment. …”
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MCFA: Multi-Scale Cascade and Feature Adaptive Alignment Network for Cross-View Geo-Localization by Kaiji Hou, Qiang Tong, Na Yan, Xiulei Liu, Shoulu Hou

“…However, they exhibit limitations in modeling the interactions among local features and fall short in aligning cross-view representations accurately. To address these issues, we propose a Multi-Scale Cascade and Feature Adaptive Alignment (MCFA) network, which consists of a Multi-Scale Cascade Module (MSCM) and a Feature Adaptive Alignment Module (FAAM). …”
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An improved EAE-DETR model for defect detection of server motherboard by Jian Chi, Mingke Zhang, Puhon Zhang, Guowang Niu, Zhihao Zheng

“…Lastly, we constructed the EUCB-SC upsampling module, which integrates depth convolution and channel shuffling strategies to enhance feature reconstruction efficiency. …”
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Stock movement prediction with multimodal stable fusion via gated cross-attention mechanism by Chang Zong, Jian Wan, Lucia Cascone, Hang Zhou

“…The MSGCA framework consists of three integral components: (1) a trimodal encoding module, responsible for processing indicator sequences, dynamic documents, and a relational graph, and standardizing their feature representations; (2) a cross-feature fusion module, where primary and consistent features guide the multimodal fusion of the three modalities via a pair of gated cross-attention networks; and (3) a prediction module, which refines the fused features through temporal and dimensional reduction to execute precise movement forecasting. …”
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Segmentation detection method in tree-shaded environment for road cracks collected by inspection vehicle on WFU-Unet by Qiong Zhang, Shilin Huang, Haomiao Wang, Zhonghang Ji, Shuang Zheng, Yunqing Liu

“…Finally, the Up module substitutes conventional upsampling techniques to minimize spatial information loss of cracks. …”
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A Latent Multi-Scale Residual Transformer Approach for Cross-Modal Medical Image Synthesis by Xinmiao Zhu, Yang Li

“…Additionally, a multi-level information fusion (MIF) module is integrated into the encoder-decoder and latent feature space, consisting of a dual-scale selective fusion (DSF) module that adaptively aggregates multi-scale information to generate target modality images. …”
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RLDD-YOLOv11n: Research on Rice Leaf Disease Detection Based on YOLOv11 by Kui Fang, Rui Zhou, Nan Deng, Cheng Li, Xinghui Zhu

“…Second, recognizing the limitations of the native upsampling module in YOLOv11n in reconstructing rice-disease-related features, the CARAFE upsampling module is incorporated. …”
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Semantic Co-Occurrence and Relationship Modeling for Remote Sensing Image Segmentation by Yinxing Zhang, Haochen Song, Qingwang Wang, Pengcheng Jin, Tao Shen

“…However, RS semantic segmentation is hindered by issues like class imbalance, occlusion, blurring, and small target sizes. …”
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A Transformer-Based Multiscale Difference Enhancement Network for Change Detection by Mengyang Pan, Hang Yang, Chengkang Yu, Mingqing Li, Anping Deng

“…This is further complemented by a cross-hierarchical linear fusion module for multiscale feature integration. Additionally, a difference enhancement module isolates and emphasizes change-related features. …”
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Novel Cricket World Cup Mass Gatherings Surveillance for Event-Based Surveillance in the Caribbean Region by Keston Daniel, Mohamed Elsherbiny, Sastee Kissoondan, Lisa Indar

“…Designs/Methods This framework, using multiple data sources, including the MG Surveillance module, provided daily intelligence and threat analysis to host nations. …”
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ANF-Net: A Refined Segmentation Network for Road Scenes with Multiple Noises and Various Morphologies of Cracks by Xiao Hu, Qihao Chen, Xiuguo Liu, Gang Deng, Cheng Chi, Bin Wang

“…However, challenges persist due to the presence of numerous noisy pixels in the image background and the diverse and intricate morphologies of cracks, leading to issues such as misclassification and omission. To address these issues, this paper proposes a refined pixel-level segmentation network (ANF-Net) suitable for complex crack detection scenarios with high noise levels and diverse crack morphologies. …”
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SDD-Net: A Steel Surface Defect Detection Method Based on Contextual Enhancement and Multiscale Feature Fusion by Chao Liang, Zi-Zheng Wang, Xiao-Lin Liu, Peng Zhang, Zhi-Wei Tian, Ru-Liang Qian

“…Addressing the current industrial methods for surface defect detection, which suffer from issues such as low detection efficiency, elevated rates of false positives, and inadequate real-time capabilities, this paper proposes an high-precision industrial defect detection network. …”
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MLGFENet: Multiscale Local–Global Feature Enhancement Network for High-Resolution Remote Sensing Image Change Detection by Huanhuan Lv, Xianqi Yan, Hui Zhang, Cuiping Shi, Ruiqin Wang

“…Subsequently, a hybrid-scale global context feature extraction module is designed. This module enables the modeling of multiscale global contextual information, thereby further enhancing the model’s feature representation capability. …”
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SAM-Net: Spatio-Temporal Sequence Typhoon Cloud Image Prediction Net with Self-Attention Memory by Yanzhao Ren, Jinyuan Ye, Xiaochuan Wang, Fengjin Xiao, Ruijun Liu

“…To address these issues, we have introduced an innovative model called SAM-Net. …”
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Assessment of a Top and Bottom Cooling Strategy for Prismatic Lithium-Ion Cells Intended for Automotive Use by Said Madaoui, Bartlomiej Guzowski, Roman Gozdur, Zlatina Dimitrova, Nicolas Audiot, Jocelyn Sabatier, Jean-Michel Vinassa, Franck Guillemard

“…In this work, a novel thermal management approach is proposed, in which a battery module is cooled not only with a bottom cooling plate but also using another cooling plate in contact with the busbars, located on the top of the battery module. …”
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A Metric Learning-Based Improved Oriented R-CNN for Wildfire Detection in Power Transmission Corridors by Xiaole Wang, Bo Wang, Peng Luo, Leixiong Wang, Yurou Wu

“…Experimental results showed that the introduction of the MCM-Loss module increased the average precision (AP) for smoke targets by 2.7%. …”
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An Improved YOLOv8-Based Method for Detecting Pests and Diseases on Cucumber Leaves in Natural Backgrounds by Jiacong Xie, Xingliu Xie, Wu Xie, Qianxin Xie

“…First, the deformable convolution network DCNv2 (Deformable Convolution Network version 2) is introduced, replacing the original C2f module with an improved C2f_DCNv2 module in the backbone feature extraction network’s final C2f block. …”
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A Joint Knowledge Extraction Model for Tobacco Pest and Disease Prevention Based on BERT+BA+CASREL by Kehan Liu, Feng Zhang, Qiulan Wu, Xiang Sun, Huarui Wu, Ziruo Sun

“…Additionally, the GHM loss function is adopted to replace the traditional cross-entropy loss function, alleviating the data imbalance issue. Experimental results demonstrate that the proposed model achieves a precision of 93.32%, a recall of 92.51%, and an F1-score of 92.91%, validating its effectiveness in addressing long-text overlapping triplet extraction and other related issues. …”
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Ship Detection Transformer in SAR Images Based on Key Scattering Points Feature Aggregation and Context Feature Refinement by Yifei Yin, Zhu Yang, Hao Shi, Fanyu Meng, Wei Li

“…Furthermore, to address the issue of excessive false alarms under complex background interference, a context feature refinement module is designed to augment the semantic representation and context information of feature maps. …”
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Research on Detection and Counting Method of Green Walnut Based on YOLOv8n-RBP by Bangbang Chen, Keke Tan, Kun Li, Baojian Ma, Xiangdong Liu

“…First, a receptive field-concentrated attention module (RFCBAM) is integrated into the backbone network to enhance feature extraction capabilities. …”
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