A Dehazing Method for UAV Remote Sensing Based on Global and Local Feature Collaboration by Chenyang Li, Suiping Zhou, Ting Wu, Jiaqi Shi, Feng Guo

“…In parallel, a local information extraction sub-network equipped with an Adaptive Local Information Enhancement (ALIE) module is used to refine texture and edge details. …”
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SERNet: Spatially Enhanced Recalibration Network for Building Extraction in Dense Remote Sensing Scenes by Kuikui Han, Yuanwei Yang, Xianjun Gao, Dongjie Yang, Lei Xu

“…The rapid development of urban and rural construction has accelerated the demand for segmentation in dense building scenes. However, the issue of inaccurate building localization in such scenes still lacks effective solutions. …”
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PR-CLIP: Cross-Modal Positional Reconstruction for Remote Sensing Image–Text Retrieval by Jihong Guan, Yulou Shu, Wengen Li, Zihan Song, Yichao Zhang

“…Specifically, PR-CLIP first uses a cross-modal positional information extraction module to extract the complementary features between images and texts. …”
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Learning From Natural Images in Few-Shot SAR Target Classification by Songhao Shi, Xiaodan Wang, Yafei Song

“…To further address the challenge of category confusion in SAR images, we introduce an embedding space reconstruction module. This module utilizes supervised contrastive learning to enhance intraclass compactness and interclass divergence of features. …”
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Application of CycleGAN-based low-light image enhancement algorithm in foreign object detection on belt conveyors in underground mines by Anxin Zhao, Qiuhong Zheng, Liang Li

“…Finally, a dynamic effective self-attention aggregation module is designed to suppress the generation of noise and artifacts. …”
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BiEHFFNet: A Water Body Detection Network for SAR Images Based on Bi-Encoder and Hybrid Feature Fusion by Bin Han, Xin Huang, Feng Xue

“…Additionally, the convolutional block attention module (CBAM) is employed to suppress irrelevant information of the output features of each ResNet stage. …”
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Influence of Climatic Parameters on the Photovoltaic Conversion Efficiency of a Polycrystalline Solar Panel by N.K. Tanasheva, A.A. Potapova, L.L. Minkov, A.S. Tussypbayeva, A.N. Dyusembaeva, E.K. Mussenova, B.B. Kutum, A.Z. Tleubergenova

“…Therefore, depending on the region and time of year, the same solar module will have different performance. Based on this, an urgent issue when planning the use of solar panels is the possibility of determining how much the efficiency of photovoltaic conversion in a particular area will decrease. …”
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Adversarial patch defense algorithm based on PatchTracker by Zhenjie XIAO, Shiyu HUANG, Feng YE, Liqing HUANG, Tianqiang HUANG

“…The application of deep neural networks in target detection has been widely adopted in various fields.However, the introduction of adversarial patch attacks, which add local perturbations to images to mislead deep neural networks, poses a significant threat to target detection systems based on vision techniques.To tackle this issue, an adversarial patch defense algorithm based on PatchTracker was proposed, leveraging the semantic differences between adversarial patches and image backgrounds.This algorithm comprised an upstream patch detector and a downstream data enhancement module.The upstream patch detector employed a YOLOV5 (you only look once-v5) model with attention mechanism to determine the locations of adversarial patches, thereby improving the detection accuracy of small-scale adversarial patches.Subsequently, the detected regions were covered with appropriate pixel values to remove the adversarial patches.This module effectively reduced the impact of adversarial examples without relying on extensive training data.The downstream data enhancement module enhanced the robustness of the target detector by modifying the model training paradigm.Finally, the image with removed patches was input into the downstream YOLOV5 target detection model, which had been enhanced through data augmentation.Cross-validation was performed on the public TT100K traffic sign dataset.Experimental results demonstrated that the proposed algorithm effectively defended against various types of generic adversarial patch attacks when compared to situations without defense measures.The algorithm improves the mean average precision (mAP) by approximately 65% when detecting adversarial patch images, effectively reducing the false negative rate of small-scale adversarial patches.Moreover, compared to existing algorithms, this approach significantly enhances the accuracy of neural networks in detecting adversarial samples.Additionally, the method exhibited excellent compatibility as it does not require modification of the downstream model structure.…”
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MPE-HRNet^<i>L</i>: A Lightweight High-Resolution Network for Multispecies Animal Pose Estimation by Jiquan Shen, Yaning Jiang, Junwei Luo, Wei Wang

“…Secondly, we construct a feature extraction module based on a mixed pooling module and a dual spatial and channel attention mechanism, and take the feature extraction module as the basic module of MPE-HRNet<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mphantom><mo>.…”
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Benthos-DETR: a high-precision efficient network for benthic organisms detection by Weibo Rao, Gang Chen, Yifei Zhang, Jue Cang, Shusen Chen, Chenyang Wang

“…In the neck, the original concatenation module is replaced with the Fusion Focus Module, effectively aggregating feature layer information from different stages of the backbone to achieve cross-scale feature fusion. …”
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YOLO-GCOF: A Lightweight Low-Altitude Drone Detection Model by Wanjun Yu, Kongxin Mo

“…YOLO-GCOF incorporates the GSConv-Integrated Dynamic Group Convolution Shuffle Transformer (GI-DGCST) module as the feature extraction module, which captures fine-grained details and improves the detection of small-scale features. …”
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Research on Technology of Optical Switch Devices with Integrated Tunable Filters by HU Di, XIAO Qingming, ZHENG Jie

“…To reduce the implementation complexity of the ROADM downstream transmission system, it is necessary to address the issue of bulky module sizes. Therefore, this article designs an OSW device integrated with TOF functionality to reduce the size of the MCS module and optimize its structure.…”
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Fine-Grained Style Alignment and Class Balance for Unsupervised Domain Adaptation in Remote Sensing Image Segmentation by Yousheng Xu, Weiji Wang, Wei Yao, Shengzhou Xu

“…In addition, class imbalance causes the model to be biased toward dominant classes, resulting in decreased overall classification accuracy. To address these issues, this article proposes two innovative modules. …”
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A speech recognition method with enhanced transformer decoder by Hengbo Hu, Tong Niu, Zhenhua He

“…The enhanced decoder separates and combines the two attention mechanisms in the Transformer decoder into cross-attention layers and a self-attention language model module. The cross-attention layers are utilized to capture local features more efficiently from the encoder output, and the self-attention language model module is used to pre-train with additional domain-related text, followed by cold fusion training. …”
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FCMI-YOLO: An efficient deep learning-based algorithm for real-time fire detection on edge devices. by Junjie Lu, Yuchen Zheng, Liwei Guan, Bing Lin, Wenzao Shi, Junyan Zhang, Yunping Wu

“…Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”
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A YOLOv8 algorithm for safety helmet wearing detection in complex environment by Chunning Song, Yinzhong Li

“…Second, a novel convolution module is proposed to help the network focus more on important feature information and improve the effectiveness of the model in feature extraction. …”
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A Tomato Recognition and Rapid Sorting System Based on Improved YOLOv10 by Weirui Liu, Su Wang, Xingjun Gao, Hui Yang

“…In order to address the issue of time-consuming, labor-intensive traditional industrial tomato sorting, this paper proposes a high-precision tomato recognition strategy and fast automatic grasping system. …”
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Semantic Segmentation of Unmanned Driving Scene Based on Spatial Channel Dual Attention by WANGXiaoyu, LINPeng

“… An important issue in the field of unmanned driving is how to run real-time high-precision semantic segmentation models on low-power mobile electronic devices. …”
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Advanced stimulation and dog behavior analysis system by Stojanović Milan, Stevanović Dejan, Stošović Slavimir

“…If the hunter needs the dog to return or to stop chasing prey, they can issue an audible or vibratory command, provided the dog has been adequately trained. …”
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Research and Design of an Active Light Source System for UAVs Based on Light Intensity Matching Model by Rui Ming, Tao Wu, Zhiyan Zhou, Haibo Luo, Shahbaz Gul Hassan

“…The system consists of three components: an environment sensing and control module, a variable active light source module, and a light source power module. …”
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