Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection by ZHENG Kaikui, JI Kangyou, LI Jun, LI Qiming

“…These feature maps capture both high-level semantic information and low-level spatial details, which are essential for detecting pedestrians in complex scenes. …”
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Review of Multivariate Time Series Clustering Algorithms by ZHENG Desheng, SUN Hanming, WANG Liyuan, DUAN Yaoxin, LI Xiaoyu

“…Initially, based on classification standards such as feature extraction methods, similarity measurement algorithms, and clustering partition frameworks, this paper conducts a comparative analysis of existing multivariate time series clustering algorithms. …”
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YOLO-PEL: The Efficient and Lightweight Vehicle Detection Method Based on YOLO Algorithm by Zhi Wang, Kaiyu Zhang, Fei Wu, Hongxiang Lv

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MHFS-FORMER: Multiple-Scale Hybrid Features Transformer for Lane Detection by Dongqi Yan, Tao Zhang

“…Furthermore, a significant drawback of most existing lane-detection algorithms lies in their reliance on complex post-processing and strong prior knowledge. …”
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Panel defect detection algorithm based on improved Faster R-CNN by Chen Wanqin, Tang Qingshan, Huang Tao

“…In view of the low precision and low efficiency of panel surface defect detection, this paper proposes an optimized defect detection algorithm based on Faster R-CNN. …”
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Lightweight Crack Automatic Detection Algorithm Based on TF-MobileNet by Jiantao Yu, Songrong Qian, Cheng Chen

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Method of detecting IRC Botnet based on the multi-features of traffic flow by Jian-en YAN, Chun-yang YUAN, Hai-yan XU, Zhao-xin ZHANG

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Rice Appearance Quality Detection Technology Based on Muti-demensional Features by XING Jian, LUO Jia-shun

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Camouflage Target Detection Method with Mutual Compensation of Local-Global Features by HE Wenhao, GE Haibo

“…In response to the above problems, this paper proposes a camouflaged target detection method based on local-global feature mutual compensation, which uses local features and global features to compensate for each other to detect camouflaged targets. …”
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Enhanced Kidney Stone Detection and Classification Using SVM and LBP Features by Hawkar K. Hama, Hamsa D. Majeed, Goran Saman Nariman

“…The feature extraction comes into action through the LBP technique as a preparation step for the SVM classifier to complete the stone detection process. …”
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A deep learning-based algorithm for the detection of personal protective equipment. by Bo Tong, Guan Li, Xiangli Bu, Yang Wang, Xingchen Yu

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FDM-RTDETR: A Multi-Scale Small Target Detection Algorithm by Hongya Wang, Yongtao Yu, Zhaoxia Tang

“…To address challenges in uncrewed aerial vehicles (UAV) object detection including complex backgrounds, severe occlusion, dense small objects, and varying lighting conditions, we propose FDM-DETR, a novel detection algorithm specifically designed for small objects in UAV imagery. …”
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Steel Surface Defect Detection Based on Improved GCHS-YOLO Algorithm by Ruiqiang Guo, Peiyong Ji, Yapin Zhang, Jingqi Hu, Wenlong Liu, Xuejian Li, Min Li

“…In this paper, we address challenges in steel surface defect inspection, such as missed detections and false detections, by proposing the GCHS-YOLO detection algorithm. …”
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YOLO-WWBi: An Optimized YOLO11 Algorithm for PCB Defect Detection by Yi Zhao, Zhidi Jiang

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Multi-scale ship detection algorithm in SAR images in complex scenes by He Shun, Wang Yuzhu, Yang Zhiwei

“…Finally, an attention mechanism is introduced to suppress background clutter and enhance feature information. The experimental results show that the detection accuracy of the proposed method on SSDD and HRSID data sets reaches 97.9% and 93.1%, respectively, and the overall performance is better than the existing mainstream object detection algorithms.…”
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YOLO-DAFS: A Composite-Enhanced Underwater Object Detection Algorithm by Shengfu Luo, Chao Dong, Guixin Dong, Rongmin Chen, Bing Zheng, Ming Xiang, Peng Zhang, Zhanwei Li

“…However, underwater environments introduce challenges, such as poor lighting, high complexity, and diverse marine organism shapes, leading to missed detections or false positives in deep learning-based algorithms. …”
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Pedestrian Detection in Fisheye Images Based on Improved YOLOv8 Algorithm by ZHU Yumin, SUN Guangling, MIAO Fei

“…In view of the problems of inaccurate positioning and insufficient detection accuracy in pedestrian detection in fisheye images in existing target detection algorithms, an improved YOLOv8 algorithm for fisheye image detection is proposed. …”
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Lightweight defect detection algorithm of tunnel lining based on knowledge distillation by Anfu Zhu, Jiaxiao Xie, Bin Wang, Heng Guo, Zilong Guo, Jie Wang, Lei Xu, SiXin Zhu, Zhanping Yang

“…Secondly, in the distillation process, the feature and output dimension results are fused to improve the detection accuracy, and the mask feature relationship is learned in the space and channel dimension to improve the real-time detection. …”
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Mine underground object detection algorithm based on TTFNet and anchor-free by Song Zhen, Qing Xuwen, Zhou Meng, Men Yuting

“…First, CenterNet and TTFNet algorithms are introduced, then pooling is introduced into CSPNet basic structure to design a lightweight feature extraction network, at the same time optimizing the feature fusion way in the original algorithm, optimizing residual shrinkage network structure, and introducing it into object detection task. …”
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YOLOGX: an improved forest fire detection algorithm based on YOLOv8 by Caixiong Li, Yue Du, Xing Zhang, Peng Wu

“…To tackle issues, including environmental sensitivity, inadequate fire source recognition, and inefficient feature extraction in existing forest fire detection algorithms, we developed a high-precision algorithm, YOLOGX. …”
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