Multi-Modal Deep Learning for Lung Cancer Detection Using Attention-Based Inception-ResNet by Mohamed Hosny, Ibrahim A. Elgendy, Mousa Ahmad Albashrawi

“…Deep learning (DL) has emerged as a powerful alternative to autonomously identify complex patterns within radiological and histopathological images. …”
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Small Target Detection Algorithm for UAV Aerial Images Based on Improved YOLOv7-tiny by ZHANG Guanghua, LI Congfa, LI Gangying, LU Weidang

“…ObjectiveUAVs provide advantages such as easy control, low cost, and good performance, and efficiently perform tasks in diverse sites and complex environments. …”
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Mitigating Container Damage and Enhancing Operational Efficiency in Global Containerisation by Sergej Jakovlev, Tomas Eglynas, Mindaugas Jusis, Valdas Jankunas, Miroslav Voznak

“…To address these concerns, we present the Impact Detection Methodology (IDM), a system designed to monitor and detect impacts in real time, enhancing operational precision and safety. …”
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Research on a Visually Assisted Efficient Blind-Guiding System and an Autonomous Shopping Guidance Robot Arm Adapted to the Complex Environment of Farmers’ Markets by Mei Liu, Yunhua Chen, Jinjun Rao, Wojciech Giernacki, Zhiming Wang, Jinbo Chen

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Nighttime Vehicle Detection Algorithm Based on Improved YOLOv7 by Fan Zhang

“…Visualization results validate the robustness of the algorithm in long-distance, multi-target, and complex lighting scenarios. This study provides a high-precision real-time detection solution for nighttime environment sensing for autonomous driving.…”
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GrainNet: efficient detection and counting of wheat grains based on an improved YOLOv7 modeling by Xin Wang, Changchun Li, Chenyi Zhao, Yinghua Jiao, Hengmao Xiang, Xifang Wu, Huabin Chai

“…Additionally, the ASF-Gather and Distribute (ASF-GD) module optimizes the feature extraction component of the original YOLOv7 network, improving the model’s robustness and accuracy in complex scenarios. Ablation experiments validate the effectiveness of the proposed methods.Compared with classic models such as Faster R-CNN, YOLOv5, YOLOv7, and YOLOv8, the GrainNet model achieves better detection performance and computational efficiency in various scenarios and adhesion levels. …”
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YOLO-GL for efficient multi-target detection in large FOV via hierarchical feature fusion by Xinyu Chen, Chengjun Dong, Tong Cui, Guangming Lv, Yan Ren

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YOLOv8n-DDSW: an efficient fish target detection network for dense underwater scenes by Jinwang Yi, Wei Han, Fangfei Lai

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UAV-DETR: An Enhanced RT-DETR Architecture for Efficient Small Object Detection in UAV Imagery by Yu Zhou, Yan Wei

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Towards Efficient SAR Ship Detection: Multi-Level Feature Fusion and Lightweight Network Design by Wei Xu, Zengyuan Guo, Pingping Huang, Weixian Tan, Zhiqi Gao

“…Thus, guided by the principles of lightweight design, robustness, and energy efficiency optimization, this study proposes a three-stage collaborative multi-level feature fusion framework to reduce model complexity without compromising detection performance. …”
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Efficient wildlife monitoring: Deep learning-based detection and counting of green turtles in coastal areas by Naoya Noguchi, Hideaki Nishizawa, Taro Shimizu, Junichi Okuyama, Shohei Kobayashi, Kazuyuki Tokuda, Hideyuki Tanaka, Satomi Kondo

“…However, accurately detecting animals remains challenging, especially in complex field environments. …”
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Investigation of an Efficient Multi-Class Cotton Leaf Disease Detection Algorithm That Leverages YOLOv11 by Fangyu Hu, Mairheba Abula, Di Wang, Xuan Li, Ning Yan, Qu Xie, Xuedong Zhang

“…By integrating a medical image segmentation model, it effectively tackles challenges including complex background interference, the missed detection of small targets, and restricted generalization ability. …”
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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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Reliable and efficient magnetic data inversion for resource detection using a hybrid bat algorithm by Khalid S. Essa, Mahmoud Elhussein, Omar A. Gomaa, Zein E. Diab

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Enhancing Real-Time Road Object Detection: The RD-YOLO Algorithm With Higher Precision and Efficiency by Weijian Wang, Wei Yu

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CSCP-YOLO: A Lightweight and Efficient Algorithm for Real-Time Steel Surface Defect Detection by Chenglong Wang, Heng Wang, Yimin Jiang, Lei Yu, Xueting Wang

“…Steel surface defect detection is critical for ensuring product quality, yet remains challenging due to multi-scale defects, small target prevalence, and complex background interference. …”
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YOLO-Air: An Efficient Deep Learning Network for Small Object Detection in Drone-Based Imagery by Jigang Qiu, Fangkai Cai, Ning Fu, Yuanfei Yao

“…However, it poses unique challenges for object detection due to small objects, complex backgrounds, and noise interference. …”
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Lightweight patch-level attention for efficient pig behavior detection: A novel dataset and approach by Shuo Wan, Zhongqiang Huang, Tao Han, Ying Sha

“…The pig farming industry plays a crucial role in food production system. Pig behavior detection facilitates timely anomaly detection, enhances farming efficiency, ensures animal welfare, and prevents diseases. …”
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Efficient fault diagnosis in rolling bearings lightweight hybrid model by Peng Yang, Bozheng Zhang, Jianda Zhao

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Efficient removal of estradiol using MnFe2O4 microsphere and potassium persulfate complex salt by Weiwei Yu, Ting Ai, Weizhe Sun, Shuo Yang, Yufeng Mao, JiangLin Tan, Feng Yu, Chen Yin, Qin Jiang, Chengye Yu, Shiling Chen

“…Abstract In this study, MnFe2O4 microspheres were synthesized to activate potassium persulfate complex salt (Oxone) for the degradation of 17β-estradiol (17β-E2) in aqueous solutions. …”
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