A Scene Knowledge Integrating Network for Transmission Line Multi-Fitting Detection by Xinhang Chen, Xinsheng Xu, Jing Xu, Wenjie Zheng, Qianming Wang

“…Aiming at the severe occlusion problem and the tiny-scale object problem in the multi-fitting detection task, the Scene Knowledge Integrating Network (SKIN), including the scene filter module (SFM) and scene structure information module (SSIM) is proposed. …”
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Deep Learning-Based Intelligent Detection Algorithm for Surface Disease in Concrete Buildings by Jing Gu, Yijuan Pan, Jingjing Zhang

“…Finally, to address problems of missed detection, such as inadequate extraction of small targets, we extended the original YOLOv8 architecture by adding a layer in the feature extraction phase dedicated to small-target detection. …”
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FUR-DETR: A Lightweight Detection Model for Fixed-Wing UAV Recovery by Yu Yao, Jun Wu, Yisheng Hao, Zhen Huang, Zixuan Yin, Jiajing Xu, Honglin Chen, Jiahua Pi

“…Secondly, an adaptive multiscale feature pyramid network (AMFPN) is designed, which effectively integrates different scales of information through multi-level feature fusion and information transmission mechanism, alleviates the problem of information loss in small-target detection, and improves the detection accuracy in complex backgrounds. …”
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Machine learning for Internet of things anomaly detection under low-quality data by Shangbin Han, Qianhong Wu, Yang Yang

“…Therefore, practitioners may not know which algorithm to choose due to the lack of review and evaluation of anomaly detection methods under low-quality data. To address this problem, we give a detailed review and evaluation of six supervised anomaly detection methods, as well as release the core code of feature extractor for pcap format traffic traces and anomaly detection methods for reuse. …”
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MicroRNA: a clinician's view of the state of the problem. Part 2. MicroRNA as a biomarker by O. Iu. Mironova, M. V. Berdysheva, E. M. Elfimova

“…Search for sensitive and specific biomarkers is one of the most important problems in the field of diagnosis of cardiovascular diseases. …”
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GCB‐YOLO: A Lightweight Algorithm for Wind Turbine Blade Defect Detection by Zhiming Zhang, Chaoyi Dong, Ze Wei, Xiaoyan Chen, Weidong Zan, Yao Xue

“…To address this problem, this paper introduces a lightweight wind turbine blade defect detection network, GCB‐YOLO, which attempts to maintain high detection accuracy and simultaneously achieve rapid detection speed. …”
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A lightweight deep-learning model for parasite egg detection in microscopy images by Wenbin Xu, Qiang Zhai, Jizhong Liu, Xingyu Xu, Jing Hua

“…Abstract Background Intestinal parasitic infections are still a serious public health problem in developing countries, and the diagnosis of parasitic infections requires the first step of parasite/egg detection of samples. …”
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A LiDAR - camera fusion detection method based on weight allocation by Kang Haotian, Wang Tianshu

“…In automatic driving target detection problem, the neural network is applied to two methods, vision, and LiDAR. …”
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Traffic Sign Detection via Improved Sparse R-CNN for Autonomous Vehicles by Tianjiao Liang, Hong Bao, Weiguo Pan, Feng Pan

“…To tackle this problem, this study proposed an improved sparse R-CNN that integrates coordinate attention block with ResNeSt and builds a feature pyramid to modify the backbone, which enables the extracted features to focus on important information, and improves the detection accuracy. …”
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Efficient-Deformable-DETR: Enhancing underwater small target detection in complex environments by Xie Haozheng, Xin Guanghong, Kang Shuo, Xie Qiongdan

“…This paper focuses on the problem of small target detection in complex underwater environments and proposes an improved model based on the Deformable-DETR model. …”
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A novel pedestrian detection algorithm based on data fusion of face images by Jianhu Zheng, Jinshuan Peng

“…Face recognition is the most popular method to detect and track pedestrian movement. During the face recognition process, feature classification ability and reliability are determined by the feature extraction methods. …”
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Remote Sensing Image Detection Method Combining Dynamic Convolution and Attention Mechanism by Yunfei Zhang, Ming Chen, Cong Chen

“…To address the resolution loss issue in small object detection, we adopted the CARAFE (Content-Aware ReAssembly of FEatures) upsampling operator. …”
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RGB-D salient object detection based on BC2 FNet network by WANG Feng, CHENG Yongmei

“…Aiming at this problem, a boundary-driven cross-modal and cross-layer fusion network (BC2FNet) for RGB-D salient object detection is proposed in this paper, which preserves the boundary of the object by adding the guidance of boundary information to the cross-modal and cross-layer fusion, respectively. …”
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Infrared small target detection algorithm with U-shaped multiscale transformer network by DUAN Peipei, ZHANG Yan, LUO Mingshi, YAN Xiaoying

“…To solve the problem of small targets feature extraction and the susceptibility of targets to being overwhelmed by noise and complex backgrounds, a detection method with U-shaped multiscale transformer network is proposed. …”
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A Novel Quadrilateral Contour Disentangled Algorithm for Industrial Instrument Reading Detection by Xiang Li, Changchang Zeng, Yong Yao, Jide Qian, Haiding Zhang, Sen Zhang, Suixian Yang

“…However, existing methods fail to accurately read the display automatically due to incorrect labeling of the target box vertices, which arises from the vertex entanglement problem. To address these challenges, a novel Quadrilateral Contour Disentangled Detection Network (QCDNet) is proposed in this paper, which utilizes the quadrilateral disentanglement idea. …”
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Detection Method for Bolts with Mission Pins on Transmission Lines Based on DBSCAN-FPN by Zhenbing ZHAO, Shuai ZHANG, Wei JIANG, Peng WU

“…As the bolt with missing pins are small targets, their positioning is difficult and their features are hard to extract. Aim at this problem, a detection method for bolts with missing pins is proposed based on the DBSCAN algorithm and FPN model. …”
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Research on underwater target detection error compensation based on improved binocular vision by Wenhui Wang, Fumeng Ye, Yumin Peng, Shi Dong

“…A novel binocular vision error compensation method is proposed to solve the major error compensation problem caused by nonlinear distortion of camera and projector on underwater target detection. …”
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Efficient DDoS attack detection and prevention scheme based on SDN in cloud environment by Heng HE, Yan HU, Lianghan ZHENG, Zhengyuan XUE

“…For addressing the problem of two typical types of distributed denial of service (DDoS) attacks in cloud environment,a DDoS attack detection and prevention scheme called SDCC based on software defined network (SDN) architecture was proposed.SDCC used a combination of bandwidth detection and data flow detection,utilized confidence-based filtering (CBF) method to calculate the CBF score of packets,judged the packet of CBF score below the threshold as an attacking packet,added its attribute information to the attack flow feature library,and sent the flow table to intercept it through SDN controller.Simulation results show that SDCC can detect and prevent different types of DDoS attacks effectively,and it has high detection efficiency,reduces the controller’s computation overhead,and achieves a low false positive rate.…”
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Credit card fraud detection in the era of disruptive technologies: A systematic review by Asma Cherif, Arwa Badhib, Heyfa Ammar, Suhair Alshehri, Manal Kalkatawi, Abdessamad Imine

“…The selection of 40 relevant articles is reviewed and categorized according to the topics covered (class imbalance problem, feature engineering, etc.) and the machine learning technology used (modelling traditional and deep learning). …”
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Rolling window for detecting multiple Chan signatures to diagnose excessive water production by Ahmed MohamedSalih Musa Hamdoon, A. P. Mohammed Abdalla Ayoub Mohammed, A. P. Khaled Abdalla Elraies

“…A successful interactive model with the rolling window feature was developed to track slope changes in Chan signatures, resulting in a 7–10% improvement in pattern detection accuracy compared to static features. …”
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