Mitigating Catastrophic Forgetting in Pest Detection Through Adaptive Response Distillation by Hongjun Zhang, Zhendong Yin, Dasen Li, Yanlong Zhao

“…Pest detection in agriculture faces the challenge of adapting to new pest species while preserving the ability to recognize previously learned ones. …”
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Enhancing, Refining, and Fusing: Towards Robust Multiscale and Dense Ship Detection by Congxia Zhao, Xiongjun Fu, Jian Dong, Shen Cao, Chunyan Zhang

“…To address these issues, we propose a novel framework, Center-Aware SAR Ship Detector (CASS-Det), designed for robust multiscale and densely packed ship detection. CASS-Det integrates three key innovations: 1) a center enhancement module (CEM) that employs rotational convolution to emphasize ship centers, improving localization while suppressing background interference; 2) a neighbor attention module that leverages cross-layer dependencies to refine ship boundaries in densely populated scenes; and 3) a cross-connected feature pyramid network (CC-FPN) that enhances multiscale feature fusion by integrating shallow and deep features. …”
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Benchmark Dataset for AI-Driven Palm Tree Detection and Analysis in the UAE by M. Al-Saad, N. Aburaed, M. Q. Alkhatib, M. S. Zitouni, S. Almansoori, H. Al-Ahmad

“…YOLOv5s achieved outstanding performance, with an Average Precision (AP) of 96.6% and Average F1- score (AF) of 95.7%, demonstrating its effectiveness in accurately detecting and localizing palm trees. Moreover, model outputs are effectively integrated into Geographic Information Systems (GIS) for enhanced spatial analysis and monitoring.…”
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SR-DETR: Target Detection in Maritime Rescue from UAV Imagery by Yuling Liu, Yan Wei

“…By refining spatial attention mechanisms, the module significantly boosts cross-scale target recognition capabilities in the model, especially offering advantages for detecting smaller objects. To improve localization precision, we develop a novel loss function for bounding box regression, named Focaler-GIoU, which performs particularly well when handling densely packed and small-scale objects. …”
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Unsupervised Domain Adaptation for SAR Ship Detection Based on Multitask Decoupling by Yirong Yang, Xi Yang, Dong Yang

“…In domain adaptation object detection, conflict arises between transferability required for adaptation and discriminability required for detection. …”
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An Adapter and Segmentation Network-Based Approach for Automated Atmospheric Front Detection by Xinya Ding, Xuan Peng, Yanguang Xue, Liang Zhang, Tianying Wang, Yunpeng Zhang

“…This study presents AD-MRCNN, an advanced deep learning framework for automated atmospheric front detection that addresses two critical limitations in existing methods. …”
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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

“…This change improves the model’s adaptability to targets of varying scales and enhances its ability to extract key defective features.Continue to introduce the Coordinate Attention (CA) mechanism, which integrates location information to improve feature extraction, aiding in better regression and localization. This boosts the network’s ability to identify and detect defects with greater accuracy. …”
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FDAE: Lightweight Privacy Protection Based on Face Detection and Image Encryption by Li You, Qianqian Liu, Shuai Li, Tianyu Yang

“…Specifically, we developed a YOLOv7-based face detection algorithm, further enhanced with Explicit Visual Center (EVC) and Spatial Context Pyramid (SCP) modules, to accurately localize facial regions. …”
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Steel surface defect detection method based on improved YOLOv9 by Cong Chen, Hoileong Lee, Ming Chen

“…This often results in high false detection and missed detection rates during the inspection process. …”
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Damage Detection Method for Road Ancillary Facilities Integrating Attention Mechanism by Shuang Yang, Huiqin Wang, Ke Wang, Nan Guo

“…Additionally, the improved AR-BiFormer attention mechanism is integrated into the backbone network, enabling adaptive weight adjustment of feature maps through parallel processing of contextual information, thereby effectively improving the detection of small targets in complex scenes. Lastly, the WIoUv3 bounding box loss function is employed to optimize the regression performance of bounding boxes, ensuring higher localization accuracy under different scales and overlap conditions. …”
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An enhanced substation equipment detection method based on distributed federated learning by Zhuyun Li, Qiutong Qin, Yingyi Yang, Xiaoming Mai, Yuya Ieiri, Osamu Yoshie

“…We propose CWA-YOLO, a detection framework integrating multi-scale feature fusion and an enhanced small-object detection head into YOLOv8 to improve accuracy across variable conditions. …”
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Big Data-Driven Deep Learning Ensembler for DDoS Attack Detection by Abdulrahman A. Alshdadi, Abdulwahab Ali Almazroi, Nasir Ayub, Miltiadis D. Lytras, Eesa Alsolami, Faisal S. Alsubaei

“…This paper proposes EffiGRU-GhostNet, a deep-learning ensemble model for high-accuracy DDoS detection with minimal resource consumption. EffiGRU-GhostNet integrates Gated Recurrent Units (GRU) with the GhostNet architecture, optimized through Principal Component Analysis with Locality Preserving Projections (PCA-LLP) to handle large-scale data effectively. …”
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Multi-Scale Feature Fusion Model for Bridge Appearance Defect Detection by Rong Pang, Yan Yang, Aiguo Huang, Yan Liu, Peng Zhang, Guangwu Tang

“…First, the Faster R-CNN model adopts Region Of Interest (ROI) pooling, which omits the edge information of the target area, resulting in some missed detections and inaccuracies in both detecting and localizing bridge defects. …”
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Balancing complexity and accuracy for defect detection on filters with an improved RT-DETR by Maoyuan Zhang, Xiaojuan Wei, Guojun Liu, Mengxu Chen, Chunxia Zhao, Yingxiao Liu, Zhikang Bao, Yunfeng Guo, Run An, Pengcheng Zhao

“…However, existing defect detection algorithms often struggle to balance between detection accuracy and the computational efficiency required for industrial deployment. …”
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Natural Scene Text Detection With Multiscale Feature Augmentation and Attention Mechanisms by Guogang Wang, Ruilin Wang, Meiyan Liang, Shen Wei, Xin Zhao, Dan Yang, Zhongjie Wang

“…Recently, the DB algorithm has drawn considerable attention in scene text detection due to its differentiable binarization module, which is proposed to simplify the complex post-processing of the existing segmentation-based scene text detection approaches. …”
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An Investigation of Infrared Small Target Detection by Using the SPT–YOLO Technique by Yongjun Qi, Shaohua Yang, Zhengzheng Jia, Yuanmeng Song, Jie Zhu, Xin Liu, Hongxing Zheng

“…Furthermore, x-small detection heads are added, the understanding of the overall characteristics and structure of the target is enhanced much more, and the representation and localization of small targets have been improved. …”
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Development of the relationship between visual selective attention and auditory change detection by Yuanjun Kong, Xuye Yuan, Yiqing Hu, Bingkun Li, Dongwei Li, Jialiang Guo, Meirong Sun, Yan Song

“…Our one recent study has shown a positive correlation between the event-related potential (ERP) amplitudes associated with visual selective attention (posterior contralateral N2) and auditory change detection (mismatch negativity) in adults, suggesting an intimate relationship and potential shared mechanism between visual selective attention and auditory change detection. …”
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Automatic detection of lucky bamboo nodes based on Improved YOLOv7 by Jing Zhang, Jing Zhang, Jing Zhang, Ruoling Deng, Ruoling Deng, Ruoling Deng, Chengzhi Cai, Erpeng Zou, Haitao Liu, Haitao Liu, Mingxin Hou, Xinzhi Chen, Huamin Lin, Zhenye Wei

“…IntroductionThe detection of lucky bamboo (Dracaena sanderiana) nodes is a critical prerequisite for machining bamboo into high-value handicrafts. …”
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Detection and Geolocation of Peat Fires Using Thermal Infrared Cameras on Drones by Temitope Sam-Odusina, Petrisly Perkasa, Carl Chalmers, Paul Fergus, Steven N. Longmore, Serge A. Wich

“…In areas with limited accessibility and periods of thick haze and fog, these fires are difficult to detect, localize, and tackle. To address this problem, thermal infrared cameras mounted on drones can provide a potential solution since they allow large areas to be surveyed relatively quickly and can detect thermal radiation from fires above and below the peat surface. …”
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The Possibilities of Modern Ultrasound Scanning in Uveal Melanoma Extrascleral Growth Detection by A. G. Amiryan, S. V. Saakyan, G. P. Zakharova, A. Yu. Tsygankov

“…To determine the possibilities of modern ultrasound methods in the detection of uveal melanoma (UM) extrascleral growth (EG).Patients and methods. …”
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