Multi-View Attention Network With Iterative Feature Refinement and Boundary Awareness for Endoscopic Image Segmentation by Dongzhi He, Rui Zhang, Yu Liang, Jiaping Chen, Yunqi Li

“…However, achieving accurate segmentation is challenging due to issues such as boundary blurring, low contrast, and small lesion sizes. …”
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Urban Functional Zone Identification Based on Multimodal Data Fusion: A Case Study of Chongqing’s Central Urban Area by Yongchuan Zhang, Yuhong Xu, Jie Gao, Zunya Zhao, Jing Sun, Fengyun Mu

“…Finally, the method deeply fuses these features through a feature fusion module, which utilizes a two-layer fully connected network for deep fusion, allowing the model to fully utilize the interdependencies among the data types, significantly improving the UFZ classification accuracy. …”
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Mapping Biodiversity Conservation Priorities for Protected Areas for Spatial Optimization: A Case Study in the Songnen Plain, China by Qiaoyun Sun, Jianqi Yu, Yingran Zeng, Yifang Gai, Jia Wang, Yujun Zhang

“…ABSTRACT The decline in biodiversity poses a serious threat to natural ecosystems and has become one of the most pressing global environmental issues. Establishing conservation priorities for protected areas (PAs) is one of the most direct and effective biodiversity conservation measures. …”
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Lightweight highland barley detection based on improved YOLOv5 by Minghui Cai, Hui Deng, Jianwei Cai, Weipeng Guo, Zhipeng Hu, Dongzheng Yu, Houxi Zhang

“…In addition, the integration of convolutional block attention module (CBAM) enhances the model’s ability to focus on target object in complex backgrounds. …”
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Joint Classification of Hyperspectral and LiDAR Data via Multiprobability Decision Fusion Method by Tao Chen, Sizuo Chen, Luying Chen, Huayue Chen, Bochuan Zheng, Wu Deng

“…In the multifeature extraction module, the local texture features and spatial features of the image are extracted to consider the local texture and spatial structure of the image data. …”
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Low-light image enhancement method for underground mines based on an improved Zero-DCE model by WANG Yiwei, LI Xiaoyu, WENG Zhi, BAI Fengshan

“…A Convolutional Block Attention Module (CBAM) was introduced at the skip connections between the shallow and deep networks of the Zero-DCE model to enhance the model's ability to capture key image features. …”
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Fire and Smoke Detection Based on Improved YOLOV11 by Zhipeng Xue, Lingyun Kong, Haiyang Wu, Jiale Chen

“…However, complex backgrounds, large environmental changes, and data requirements pose great challenges to high-precision outdoor smoke detection. To address these issues, this paper proposes an improved model, YOLOV11-DH3, based on YOLOV11. …”
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Integrating Pose Features and Cross-Relationship Learning for Human–Object Interaction Detection by Lang Wu, Jie Li, Shuqin Li, Yu Ding, Meng Zhou, Yuntao Shi

“…Methods: In this paper, we design a Pose-Aware Interaction Network (PAIN) based on transformer architecture and human posture to address these issues through two innovations: A new feature fusion method is proposed, which fuses human pose features and image features early before the encoder to improve the feature expression ability, and the individual motion-related features are additionally strengthened by adding to the human branch; the Cross-Attention Relationship fusion Module (CARM) better fuses the three-branch output and captures the detailed relationship information of HOI. …”
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Research on Foreign Object Intrusion Detection for Railway Tracks Utilizing Risk Assessment and YOLO Detection by Shanping Ning, Rui Guo, Pengfei Guo, Lu Xiong, Bangbang Chen

“…Furthermore, a BiFPN-Lite module is introduced to fuse more target features without increasing complexity, with YOLO Head utilized to output the type information of foreign objects on the track surface. …”
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NGSTGAN: N-Gram Swin Transformer and Multi-Attention U-Net Discriminator for Efficient Multi-Spectral Remote Sensing Image Super-Resolution by Chao Zhan, Chunyang Wang, Bibo Lu, Wei Yang, Xian Zhang, Gaige Wang

“…The discriminator enhances attention to multi-scale key features through the addition of channel, spatial, and pixel attention (CSPA) modules, while the generator utilizes an improved shallow feature extraction (ISFE) module to extract multi-scale and multi-directional features, enhancing the capture of complex textures and details. …”
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Assessment of Routine Immunization Program at Selected Urban Health Centres in Ahmedabad, Gujarat, India by Jinalben Nogas, Karankumar Desai, Nandan Shah, Mitesh Patel, Shivam Chauhan, Bhavesh Gelot

“…Conclusion: The study highlights certain issues at UHC like maintenance of drop out chart, map of catchment area, training of medical officers on module of immunization, ice-packs arrangement in Deep Freeze, no knowledge of VCCHs about shake test, which indicates lack of efficiency of VCCHs and need of their training.…”
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A low illumination target detection method based on a dynamic gradient gain allocation strategy by Zhiqiang Li, Jian Xiang, Jiawen Duan

“…Secondly, by designing a new feature aggregation module, it can simultaneously fuse channel and spatial information as well as local and global information to improve the representation of the network. …”
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Re-Parameterization After Pruning: Lightweight Algorithm Based on UAV Remote Sensing Target Detection by Yang Yang, Pinde Song, Yongchao Wang, Lijia Cao

“…Consequently, this paper presents a refined iteration of the lightweight object detection algorithm to address the above issues. The MobileNetV3 based on the efficient channel attention (ECA) module is used as the backbone network of the model. …”
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Implementation of a Digital Model of Thermal Characteristics Based on the Temperature Field by V. V. Pozevalkin, A. N. Polyakov

“…However, the scientific literature does not widely present the results of research aimed at implementing digital twin technology in the design process. The general issues related to the use of digital twins in various industries are mainly considered. …”
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Nondestructive freshness recognition of chicken breast meat based on deep learning by Rui Jian, Guangbo Li, Xie Jun, Guolong Shi

“…Traditional methods for chicken breast freshness recognition suffer from issues such as high cost, difficulty in recognition, and low efficiency. …”
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Research on Abnormal Ship Brightness Temperature Detection Based on Infrared Image Edge-Enhanced Segmentation Network by Xiaobin Hong, Guanqiao Chen, Yuanming Chen, Ruimou Cai

“…The Sobel operator is used to obtain edge feature maps, and the Convolutional Block Attention Module (CBAM) extracts key feature information. In the Fusion Unit, edge features guide the extraction of infrared ship features in the backbone network, resulting in feature maps rich in edge information. …”
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Pavement pothole detection system based on deep learning and binocular vision by Tian Guan, Jianyuan Cai, Yu Wang, Wei Yang, Xiaobo Chang, Yi Han

“…The experimental results show that the system can meet the needs of unmanned vehicles, enabling them to perceive potholes in advance, thereby issuing timely warnings to drivers.…”
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BCTDNet: Building Change-Type Detection Networks with the Segment Anything Model in Remote Sensing Images by Wei Zhang, Jinsong Li, Shuaipeng Wang, Jianhua Wan

“…Moreover, an interactive attention module bridges SAM with a Convolutional Neural Network, enabling seamless interaction between fine-grained structural information and deep semantic features. …”
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Intelligent Monitoring of BECS Conveyors via Vision and the IoT for Safety and Separation Efficiency by Shohreh Kia, Benjamin Leiding

“…Simultaneously, a machine vision module autonomously detects and corrects belt misalignment, eliminating the need for manual intervention and reducing the risk of worker exposure to moving mechanical parts. …”
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A Lightweight Network for UAV Multi-Scale Feature Fusion-Based Object Detection by Sheng Deng, Yaping Wan

“…To tackle the issues of small target sizes, missed detections, and false alarms in aerial drone imagery, alongside the constraints posed by limited hardware resources during model deployment, a streamlined object detection approach is proposed to enhance the performance of YOLOv8s. …”
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