GES-YOLO: A Light-Weight and Efficient Method for Conveyor Belt Deviation Detection in Mining Environments by Hongwei Wang, Ziming Kou, Yandong Wang

“…The core of this algorithm is to enhance the model’s ability to extract features in complex scenarios, thereby improving the detection efficiency. …”
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A study on an efficient citrus Huanglong disease detection algorithm based on three-channel aggregated attention by Yizong Wang, Zhengrong Xiao, Hong Wang, Fei Li, Jiya Tian

“…Background Aiming at the problems of complex and diverse field symptoms of citrus Huanglong disease (HLB), low efficiency and insufficient recognition accuracy of traditional detection methods, this study proposes an efficient detection algorithm based on improved You Only Look Once (YOLO)v8. …”
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Efficient deep learning-based tomato leaf disease detection through global and local feature fusion by Hao Sun, Rui Fu, Xuewei Wang, Yongtang Wu, Mohammed Abdulhakim Al-Absi, Zhenqi Cheng, Qian Chen, Yumei Sun

“…To address these challenges, this study proposes an efficient Tomato Disease Detection Network (E-TomatoDet), which enhances tomato leaf disease detection effectiveness by integrating and amplifying global and local feature perception capabilities. …”
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MXT-YOLOv7t: An Efficient Real-Time Object Detection for Autonomous Driving in Mixed Traffic Environments by Afdhal Afdhal, Khairun Saddami, Mirshal Arief, Sugiarto Sugiarto, Zahrul Fuadi, Nasaruddin Nasaruddin

“…To address this problem, we present the MXT-Dataset, a novel dataset that captures the complexities of real-world mixed traffic scenarios. We also propose MXT-YOLOv7t, a real-time object detection model designed to efficiently and effectively handle the various challenges in mixed traffic scenarios. …”
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Efficient Structural Damage Detection with Minimal Input Data: Leveraging Fewer Sensors and Addressing Model Uncertainties by Fredi Alegría, Eladio Martínez, Claudia Cortés-García, Quirino Estrada, Andrés Blanco-Ortega, Mario Ponce-Silva

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An efficient algorithm for pedestrian fall detection in various image degradation scenarios based on YOLOv8n by Jianhui Xun, Xuefeng Wang, Xiufang Wang, Xiaoliang Fan, Peishuai Yang, Zhifei Zhang

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LRDS-YOLO enhances small object detection in UAV aerial images with a lightweight and efficient design by Yuqi Han, Chengcheng Wang, Hui Luo, Huihua Wang, Zaiqing Chen, Yuelong Xia, Lijun Yun

“…Abstract Small object detection in UAV aerial images is challenging due to low contrast, complex backgrounds, and limited computational resources. …”
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Toward Efficient UAV-Based Small Object Detection: A Lightweight Network with Enhanced Feature Fusion by Xingyu Di, Kangning Cui, Rui-Feng Wang

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YOLORM: An Advanced Key Point Detection Method for Accurate and Efficient Rotameter Reading in Low Flow Environments by Huang Yong, Xia Xing, Xiao Shengwang

“…Automatic reading of rotameters in low flow and challenging environments poses substantial accuracy and efficiency challenges. To address these issues, this study introduces YOLORM, an advanced key point detection method for rotameters, built upon the YOLOv8n model. …”
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Resource-Constrained Specific Emitter Identification Based on Efficient Design and Network Compression by Mengtao Wang, Shengliang Fang, Youchen Fan, Shunhu Hou

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WCANet: An Efficient and Lightweight Weight Coordinated Adaptive Detection Network for UAV Inspection of Transmission Line Accessories by Jiawei Chen, Pengfei Shi, Mengyao Xu, Yuanxue Xin, Xinnan Fan, Jinbo Zhang

“…Existing network models suffer from issues like low precision in accessory detection, elevated model complexity, and a narrow range of category detection, especially in UAV-based inspection scenarios. …”
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Lights-Transformer: An Efficient Transformer-Based Landslide Detection Model for High-Resolution Remote Sensing Images by Xu Wu, Xuqing Ren, Donghao Zhai, Xiangpeng Wang, Mehreen Tarif

“…However, existing models often face challenges, such as incomplete feature extraction, loss of contextual information, and high computational complexity. To overcome these challenges, we propose an innovative landslide detection model, Lights-Transformer, which is designed to improve both the accuracy and efficiency. …”
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Coherent Detection of Non-Orthogonal Spectrally Efficient Multicarrier Signals Using a Decision Feedback Algorithm by S. B. Makarov, S. V. Zavjalov, D. C. Nguyen, A. S. Ovsyannikova

“…At the same time, the efficiency of the detection algorithm with decision feedback turns out to be significantly lower than that when using the detection algorithm MLSE.Conclusion. …”
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A Lightweight Multi-Scale Context Detail Network for Efficient Target Detection in Resource-Constrained Environments by Kaipeng Wang, Guanglin He, Xinmin Li

“…Moreover, the need for solutions suitable for edge computing environments, which have limited computational resources, adds complexity to the task. To meet these challenges, we propose MSCDNet (Multi-Scale Context Detail Network), an innovative and lightweight architecture designed specifically for efficient target detection in such environments. …”
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PVD-GSTPS: design of an efficient parallel vehicle detection based green signal time prediction system by Nikhil Nigam, Dhirendra Pratap Singh, Jaytrilok Choudhary, Surendra Solanki

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MultiDistiller: Efficient Multimodal 3D Detection via Knowledge Distillation for Drones and Autonomous Vehicles by Binghui Yang, Tao Tao, Wenfei Wu, Yongjun Zhang, Xiuyuan Meng, Jianfeng Yang

“…Although significant progress has been made in detection methods based on point clouds, cameras, and multimodal fusion, the computational complexity of existing high-precision models struggles to meet the real-time requirements of vehicular edge devices. …”
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An Evolutionary Deep Reinforcement Learning-Based Framework for Efficient Anomaly Detection in Smart Power Distribution Grids by Mohammad Mehdi Sharifi Nevisi, Mehrdad Shoeibi, Francisco Hernando-Gallego, Diego Martín, Sarvenaz Sadat Khatami

“…The increasing complexity of modern smart power distribution systems (SPDSs) has made anomaly detection a significant challenge, as these systems generate vast amounts of heterogeneous and time-dependent data. …”
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Optimizing Input Selection for Cardiac Model Training and Inference: An Efficient 3D Convolutional Neural Networks-Based Approach to Automate Coronary Angiogram Video Selection by Shih-Sheng Chang, MD, PhD, Behrouz Rostami, PhD, Gerardo LoRusso, MD, Chia-Hao Liu, MD, Mohamad Alkhouli, MD

“…Objective: To develop an efficient and automated method for selecting appropriate coronary angiography videos for training deep learning models, thereby improving the accuracy and efficiency of medical image analysis. …”
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Streamlining Deep Learning Network for Real-time Sea Turtle Detection by Muhamad Dwisnanto Putro, Yuliana Mose, Alex Copernikus Andaria, Jane Litouw, Vecky Canisius Poekoel, Xaverius Najoan

“…A new turtle dataset is proposed that contains lighting, blur, occlusion, and complex background challenges. The evaluation results show that the proposed model performs higher accuracy than other lightweight object detection models. …”
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Apple Pest and Disease Detection Network with Partial Multi-Scale Feature Extraction and Efficient Hierarchical Feature Fusion by Weihao Bao, Fuquan Zhang

“…To address this issue, this study proposes an improved pest and disease detection algorithm, YOLO-PEL, based on YOLOv11, which integrates multiple innovative modules, including PMFEM, EHFPN, and LKAP, combined with data augmentation strategies, significantly improving detection accuracy and efficiency in complex environments. …”
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