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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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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CGADNet: A Lightweight, Real-Time, and Robust Crosswalk and Guide Arrow Detection Network for Complex Scenes by Guangxing Wang, Tao Lin, Xiwei Dong, Longchun Wang, Qingming Leng, Seong-Yoon Shin

“…In this study, we incorporated a novel C2f_Van module based on VanillaBlock, employed depth-separable convolution to reduce the parameters efficiently, utilized partial convolution (PConv) for lightweight FasterDetect, and utilized a bounding box regression loss with a dynamic focusing mechanism—WIoU<i>_v3</i>—to enhance the detection performance. …”
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DAF-Net: Dual-Aperture Feature Fusion Network for Aircraft Detection on Complex-Valued SAR Image by Qingbiao Meng, Youming Wu, Yuxi Suo, Tian Miao, Qingyang Ke, Xin Gao, Xian Sun

“…Aircraft detection in synthetic aperture radar (SAR) images plays a crucial role in supporting essential tasks, such as airport management and airspace monitoring. …”
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Eye contact based engagement prediction for efficient human–robot interaction by Magnus Jung, Ahmed Abdelrahman, Thorsten Hempel, Basheer Al-Tawil, Qiaoyue Yang, Sven Wachsmuth, Ayoub Al-Hamadi

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EMB-YOLO: A Lightweight Object Detection Algorithm for Isolation Switch State Detection by Haojie Chen, Lumei Su, Riben Shu, Tianyou Li, Fan Yin

“…This module is designed with a lightweight structure, aimed at reducing the computational complexity and parameter count, thereby optimizing the model’s computational efficiency. …”
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Field Trial Transmission of Time Frequency Packed DP-QPSK Superchannel With Spectral Efficiency of 6.2 bit/s/Hz by Gianluca Meloni

“…The use of low-order modulation format guarantees better robustness in terms of optical-signal-to-noise ratio (OSNR) and reduced complexity with respect to higher order formats. At the receiver side, coherent detection was used, together with iterative maximum <bold> <italic>a posteriori</italic></bold> probability (MAP) detection and decoding. …”
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Attention-Based Target Detection–You Only Look Once: A Detection Model for <i>Locusta migratoria</i> ssp. <i>manilensis</i> in Complex Environments by Peng Wang, Jiandong Fang, Xiuling Wang, Yudong Zhao

“…Aiming at the problem of false detection and missed detection caused by locust occlusion and background similarity in complex field environments, this paper proposes a lightweight Attention-based Target Detection (ATD) model while constructing the dataset Real-Locust with the theme of <i>Locusta migratoria</i> ssp. …”
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Efficient vision transformers with edge enhancement for robust small target detection in drone-based remote sensing by Xuguang Zhu, Zhizhao Zhang

“…This study proposes a lightweight transformer-based detector, MLD-DETR, which enhances detection performance in complex scenarios through multi-scale edge enhancement and hierarchical attention mechanisms. …”
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