Oak-YOLO: A high-performance detection model for automated Oak seed defect identification. by Hao Li, Zhuqi Li, Dongkui Chen, Wangyu Wu, Xuanlong He, Hongbo Mu

“…To address this challenge, we developed a high-resolution imaging system and proposed an improved YOLO-based model named Oak-YOLO for efficient and accurate defect detection in oak seeds. …”
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YOLO-UIR: A Lightweight and Accurate Infrared Object Detection Network Using UAV Platforms by Chao Wang, Rongdi Wang, Ziwei Wu, Zetao Bian, Tao Huang

“…Within the field of remote sensing, Unmanned Aerial Vehicle (UAV) infrared object detection plays a pivotal role, especially in complex environments. …”
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Detection Method for Safety Helmet Wearing on Construction Sites Based on UAV Images and YOLOv8 by Xin Jiao, Cheng Li, Xin Zhang, Jian Fan, Zhenwei Cai, Zhenglong Zhou, Ying Wang

“…With the increasing demand for safety management on construction sites, traditional manual inspection methods for detecting helmet usage face challenges such as low efficiency, limited coverage, and strong subjectivity, making them inadequate for modern construction site safety requirements. …”
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YOLOv8n-SSDW: A Lightweight and Accurate Model for Barnyard Grass Detection in Fields by Yan Sun, Hanrui Guo, Xiaoan Chen, Mengqi Li, Bing Fang, Yingli Cao

“…Field tests using drones combined with ground-based computers further validated the model’s robustness in real-world complex paddy environments. The results indicate that YOLOv8n-SSDW exhibits excellent accuracy and efficiency. …”
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A Bio-Inspired Learning Dendritic Motion Detection Framework with Direction-Selective Horizontal Cells by Tianqi Chen, Yuki Todo, Zhiyu Qiu, Yuxiao Hua, Hiroki Sugiura, Zheng Tang

“…Comparisons with state-of-the-art (SOTA) models like vision transformers (ViTs) and convolutional neural networks (CNNs) demonstrate the HCdM’s robustness and efficiency. Additionally, in contrast to previous artificial visual systems (AVSs), our findings suggest that lateral geniculate nucleus (LGN) structures, though present in biological vision, may not be essential for motion direction detection. …”
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Multi-target detection and tracking based on CRF network and spatio-temporal attention for sports videos by Xi Chen, Hui Zhang, Achyut Shankar, Bharat Bhushan, Kireet Joshi

“…Therefore, the purpose of this article is to propose an efficient multi-target detection algorithm to quickly and effectively detect all target objects in the video. …”
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Wheat Leaf Disease Detection: A Lightweight Approach with Shallow CNN Based Feature Refinement by Oumayma Jouini, Mohamed Ould-Elhassen Aoueileyine, Kaouthar Sethom, Anis Yazidi

“…Improving agricultural productivity is essential due to rapid population growth, making early detection of crop diseases crucial. Although deep learning shows promise in smart agriculture, practical applications for identifying wheat diseases in complex backgrounds are limited. …”
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WeedSwin hierarchical vision transformer with SAM-2 for multi-stage weed detection and classification by Taminul Islam, Toqi Tahamid Sarker, Khaled R. Ahmed, Cristiana Bernardi Rankrape, Karla Gage

“…Our research evaluates several state-of-the-art object detection architectures, including DINO Transformer (with ResNet-101 and Swin backbones), Detection Transformer (DETR), EfficientNet B4, YOLO v8, and RetinaNet. …”
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Dual Improvements DCNv4 and AsDDet Mechanisms for Small Object Detection in Aerial Imagery by Fan Jiang, Hua-Ching Chen, Song-Lin Wei, Hsuan-Ming Feng

“…This integration enhances both the operational efficiency and overall performance. Furthermore, AsDDet, an efficient and innovative technique, employs an asymmetric dual-branch structure to decouple the classification and regression tasks. …”
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Synergistic Multi-Model Approach for GPR Data Interpretation: Forward Modeling and Robust Object Detection by Hang Zhang, Zhijie Ma, Xinyu Fan, Feifei Hou

“…The proposed method achieves a mean average precision (mAP) of 0.579 on synthetic datasets, outperforming YOLOv3 and RetinaNet by 16.0% and 23.5%, respectively, while maintaining robust multi-object detection in complex field conditions.…”
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A target detection model HR-YOLO for advanced driver assistance systems in foggy conditions by Yao Zhang, Na Jia

“…To enhance detection performance under complex meteorological conditions, several critical modules have been optimized. …”
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Detection of disease on nasal breath sound by new lightweight architecture: Using COVID-19 as an example by Jiayuan She, Lin Shi, Peiqi Li, Ziling Dong, Renxing Li, Shengkai Li, Liping Gu, Zhao Tong, Zhuochang Yang, Yajie Ji, Liang Feng, Jiangang Chen

“…Although many countries have reduced or stopped large-scale testing measures, the detection of such diseases remains a propriety. Objective This study aims to develop a novel, lightweight deep neural network for efficient, accurate, and cost-effective detection of COVID-19 using a nasal breathing audio data collected via smartphones. …”
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A Vision-Based Method for Detecting the Position of Stacked Goods in Automated Storage and Retrieval Systems by Chuanjun Chen, Junjie Liu, Haonan Yin, Biqing Huang

“…While computer vision and deep learning offer promising solutions, existing methods struggle to balance detection accuracy, computational efficiency, and environmental adaptability. …”
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The development of an intelligent comprehensive detection instrument for circuit breakers in power systems and its key technologies by Weimin Guan, Han Hu, Chao Sun, Jie Ji

“…Experimental results demonstrate that the intelligent detection instrument outperforms existing methods in terms of accuracy, detection efficiency, and anti-interference capabilities. …”
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Facilitating laboratory automation using a robot with a simple and inexpensive camera detection system by Rebecca Wienbruch, Nicole Rupp, Ruven Dreischke, Verena Mayer, Isabell Fenske, Rebecca Bauer, Thole Zuchner

“…Abstract Laboratory automation has transformed bioanalytical research, yet smaller research laboratories face challenges in adopting such technologies due to limited resources, time, and technical expertise, while already facing complex bioanalytical methods. To address these barriers, we developed a robotic-arm-based camera detection system featuring two software applications designed to simplify laboratory automation. …”
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A novel method of BiFormer with temporal-spatial characteristics for ECG-based PVC detection by Siyuan Chen, Zhen Wang, Hao Wang, Shuai Wang, Yang Li, Yang Li, Bing Wang

“…The use of deep learning models in electrocardiogram (ECG) analysis has aided more accurate and efficient PVC identification. These models automatically extract and analyze complex signal features, providing valuable clinical decision-making support. …”
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FFT-RDNet: A Time–Frequency-Domain-Based Intrusion Detection Model for IoT Security by Bingjie Xiang, Renguang Zheng, Kunsan Zhang, Chaopeng Li, Jiachun Zheng

“…Resource-constrained Internet of Things (IoT) devices demand efficient and robust intrusion detection systems (IDSs) to counter evolving cyber threats. …”
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YOLOv8-DEE: a high-precision model for printed circuit board defect detection by Feifan Yi, Ahmad Sufril Azlan Mohamed, Mohd Halim Mohd Noor, Fakhrozi Che Ani, Zol Effendi Zolkefli

“…Despite considerable efforts in PCB defect inspection, current detection models struggle with accuracy due to complex backgrounds and multi-scale characteristics of PCB defects. …”
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Immobilization of DNA Aptamers on Polyester Cloth for Antigen Detection by Dot Blot Immunoenzymatic Assay (Aptablot) by Sally Smiley, Maria DeRosa, Burton Blais

“…A simple dot blot immunoenzymatic assay system was developed using polyester cloth coated with an oligo-DNA aptamer to provide a high-affinity macroporous surface for the efficient capture of a model protein analyte (thrombin) in complex sample matrices such as foods. …”
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A Triple-Channel Network for Maritime Radar Targets Detection Based on Multi-Modal Features by Kaiqi Wang, Zeyu Wang

“…Sea surface target detectors are often interfered by various complex sea surface factors such as sea clutter. Especially when the signal-to-clutter ratio (SCR) is low, it is difficult to achieve high-performance detection. …”
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