Real-time and resource-efficient banana bunch detection and localization with YOLO-BRFB on edge devices by Shuo Wang, Shuo Wang, Shuo Wang, Lijiao Wei, Danran Zhang, Danran Zhang, Ling Chen, Ling Chen, Weihua Huang, Dongjie Du, Kangmin Lin, Zhenhui Zheng, Zhenhui Zheng, Zhenhui Zheng, Jieli Duan

“…Current methods face challenges in achieving high detection accuracy and efficient deployment due to their structural complexity and significant computational demands. …”
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RiceNet: Efficient CNN for High-Throughput Image-Based Rice Panicle Detection and Counting by Kushwaha Ragini, Balkrishna Sutar Manisha

“…Traditionally, therefore, accurate and efficient detection and counting of rice panicles are labor intensive. …”
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Efficient automated detection of power quality disturbances using nonsubsampled contourlet transform & PCA-SVM by Pampa Sinha, Kaushik Paul, Asit Mohanty, IM Elzein, Chandra Sekhar Mishra, Mohamed Metwally Mahmoud, Daniel Eutyche Mbadjoun Wapet, Abdulrahman Al Ayidh, Ahmed Althobaiti, Hany S Hussein, Thamer AH Alghamdi, Ahmed M Ewais

“…The increasing complexity of modern power systems, driven by smart grid technologies, dispersed generation, and renewable energy sources, has made power quality (PQ) evaluation more challenging. …”
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Accelerated and Energy-Efficient Galaxy Detection: Integrating Deep Learning with Tensor Methods for Astronomical Imaging by Humberto Farias, Guillermo Damke, Mauricio Solar, Marcelo Jaque Arancibia

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Can Separation Enhance Fusion? An Efficient Framework for Target Detection in Multimodal Remote Sensing Imagery by Yong Wang, Jiexuan Jia, Rui Liu, Qiusheng Cao, Jie Feng, Danping Li, Lei Wang

“…Leveraging this framework, we present Sep-Fusion—an efficient target detection approach tailored for multimodal remote sensing aerial imagery. …”
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Distinguishing Difficulty Imbalances in Strawberry Ripeness Instances in a Complex Farmland Environment by Yang Gan, Xuefeng Ren, Huan Liu, Yongming Chen, Ping Lin

“…The existing strawberry ripeness detection algorithm has the problems of a low precision and a high missing rate in real complex scenes. …”
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SAMF-YOLO: A self-supervised, high-precision approach for defect detection in complex industrial environments. by Jun Huang, Shamsul Arrieya Ariffin, Qiang Zhu, Wanting Xu, Qun Yang

“…As object detection models grow in complexity, balancing computational efficiency and feature expressiveness becomes a critical challenge. …”
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Synchronous End-to-End Vehicle Pedestrian Detection Algorithm Based on Improved YOLOv8 in Complex Scenarios by Shi Lei, He Yi, Jeffrey S. Sarmiento

“…To address these challenges, this paper proposes an improved vehicle and pedestrian detection algorithm based on YOLOv8, with the aim of enhancing detection in complex traffic scenes. …”
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A lightweight real-time unified detection model for rice and wheat ears in complex agricultural environments by Xiaojun Shen, Shuai Li, Fen Qiu, Lili Yao

“…Therefore, in response to the lack of research on the unified real-time detection of rice and wheat ear, this paper proposes a lightweight detection model, Light-Y, suitable for complex environments. …”
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Image small target detection in complex traffic scenes based on Yolov8 multiscale feature fusion by Xuguang Chai, Meizhi Zhao, Jing Li, Junwu Li

“…Experimental validations corroborate the efficacy and superiority of the proposed method. Enhanced detection performance is achieved, effectively mitigating the challenges of small target detection in complex scenarios, such as under poor lighting conditions in traffic environments, and elevating both the accuracy and efficiency of detection.…”
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TSD-Net: A Traffic Sign Detection Network Addressing Insufficient Perception Resolution and Complex Background by Chengcheng Ma, Chang Liu, Litao Deng, Pengfei Xu

“…By incorporating the C3k2 module and dynamic convolution into the network, the framework achieves enhanced feature extraction flexibility while maintaining high computational efficiency. Extensive experiments on the TT100K benchmark dataset demonstrate that TSD-Net outperforms most existing methods in small object detection and complex background handling, achieving 91.4 mAP and 49.7 FPS on 640 × 640 low-resolution images, meeting the requirements of practical applications.…”
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FastPFM: a multi-scale ship detection algorithm for complex scenes based on SAR images by Wei Wang, Dezhi Han, Chongqing Chen, Zhongdai Wu

“…However, various challenges, such as blurred ship contours, complex backgrounds, and uneven scale distribution, can impede detection performance improvement. …”
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YOLO11-ARAF: An Accurate and Lightweight Method for Apple Detection in Real-World Complex Orchard Environments by Yangtian Lin, Yujun Xia, Pengcheng Xia, Zhengyang Liu, Haodi Wang, Chengjin Qin, Liang Gong, Chengliang Liu

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YOLO-PGC: A Tomato Maturity Detection Algorithm Based on Improved YOLOv11 by Qian Wu, Heming Huang, Dongke Song, Jie Zhou

“…Overall, these components and strategies are integrated into YOLO-PGC to achieve robust object detection in complex scenarios.…”
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DEPDet: A Cross-Spatial Multiscale Lightweight Network for Ship Detection of SAR Images in Complex Scenes by Jing Zhang, Fan Deng, Yonghua Wang, Jie Gong, Ziyang Liu, Wenjun Liu, Yinmei Zeng, Zeqiang Chen

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Wearable devices for monitoring sweat glucose: an integrated strategy for efficient electrochemical sensors by Ruiyu Luo, Yi Yang, Shayuanzi Huang, Zhi Huang

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Detecting Planting Holes Using Improved YOLO-PH Algorithm with UAV Images by Kaiyuan Long, Shibo Li, Jiangping Long, Hui Lin, Yang Yin

“…To address this issue, a target detection network named YOLO-PH was designed to efficiently and rapidly detect planting holes in complex environments. …”
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Development of a thrombin-antithrombin complex detection kit and study in venous thromboembolism complicated by cervical cancer by Yanru Qiu, Shuang Han, Yu Ji, Zhixian Lu, Xuan Huang

“…Thrombin-antithrombin complex (TAT), fibrinolytic enzyme-α2-fibrinolytic inhibitor complex (PIC), thrombomodulin (TM), and tissue-type plasminogen activator inhibitor 1 complex (t-PAIC) were detected using quantitative chemiluminescence immunoassay. …”
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A Lightweight Model for Shine Muscat Grape Detection in Complex Environments Based on the YOLOv8 Architecture by Changlei Tian, Zhanchong Liu, Haosen Chen, Fanglong Dong, Xiaoxiang Liu, Cong Lin

“…This study addresses these challenges by proposing a lightweight YOLOv8-based model, incorporating DualConv and the novel C2f-GND module to enhance feature extraction and reduce computational complexity. Evaluated on the newly developed Shine-Muscat-Complex dataset of 4715 images, the proposed model achieved a 2.6% improvement in mean Average Precision (mAP) over YOLOv8n while reducing parameters by 36.8%, FLOPs by 34.1%, and inference time by 15%. …”
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YOLO-SBA: A Multi-Scale and Complex Background Aware Framework for Remote Sensing Target Detection by Yifei Yuan, Yingmei Wei, Xiaoyan Zhou, Yanming Guo, Jiangming Chen, Tingshuai Jiang

“…Remote sensing target detection faces significant challenges in handling multi-scale targets, with the high similarity in color and shape between targets and backgrounds in complex scenes further complicating the detection task. …”
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