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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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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A Lightweight Semantic- and Graph-Guided Network for Advanced Optical Remote Sensing Image Salient Object Detection by Jie Liu, Jinpeng He, Huaixin Chen, Ruoyu Yang, Ying Huang

“…To further efficiently aggregate multi-level features and preserve the integrity and complexity of overall object shape, we introduce a Graph-Based Region Awareness Module (GRAM). …”
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FECI-RTDETR a Lightweight Unmanned Aerial Vehicle Infrared Small Target Detector Algorithm Based on RT-DETR by Renzheng Xue, Shijie Hua, Haiqiang Xu

“…Addressing the challenges of small target detection in aerial infrared images from a drone&#x2019;s perspective, such as diverse target scales, complex backgrounds, the clustering of small targets, and limited computational resources of the drone platform. …”
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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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FLE-YOLO: A Faster, Lighter, and More Efficient Strategy for Autonomous Tower Crane Hook Detection by Xin Hu, Xiyu Wang, Yashu Chang, Jian Xiao, Hongliang Cheng, Firdaousse Abdelhad

“…To address the complexities of crane hook operating environments, the challenges faced by large-scale object detection algorithms on edge devices, and issues such as frame rate mismatch causing image delays, this paper proposes a faster, lighter, and more efficient object detection algorithm called FLE-YOLO. …”
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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

“…Abstract In the context of intelligent agriculture, tomato cultivation involves complex environments, where leaf occlusion and small disease areas significantly impede the performance of tomato leaf disease detection models. …”
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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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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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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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Hardware and Software Complex for the Study of the Joint Use of Technical Means Based on Various Physical Principles by E. I. Mikhnionok, A. V. Khizniak

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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

“…Compared to the baseline YOLOv8n model, YOLORM achieved a 7.43% increase in detection accuracy and a 15.21% reduction in computational complexity. …”
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SqueezeSlimU-Net: An Adaptive and Efficient Segmentation Architecture for Real-Time UAV Weed Detection by Alina L. Machidon, Andraz Krasovec, Veljko Pejovic, Octavian M. Machidon

“…In this article, we introduce SqueezeSlimU-Net (SSU-Net), an adaptive and efficient deep learning (DL) model designed to enhance UAV capabilities in performing complex image segmentation tasks under resource constraints, thereby advancing real-time UAV vision&#x2014;a crucial technology in fields, such as precision agriculture. …”
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BESW-YOLO: A Lightweight SAR Image Detection Model Based on YOLOv8n for Complex Scenarios by Xiao Tang, Kun Cao, Yunzhi Xia, Enkun Cui, Weining Zhao, Qiong Chen

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Phosphorescent Sensor Based on Iridium(III) Complex with Aggregation-Induced Emission Activity for Facile Detection of Volatile Acids by Yu Pei, Yan Sun, Dongxia Zhu

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