Video Analysis and Frame Prediction Based on Improved Object Detection and ConvGRU by Xijuan Wang, Ru Chen

“…The loss function and average accuracy mean have been improved, with a maximum detection accuracy of 0.947. …”
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BDK-YOLOv8: An Enhanced Algorithm for UAV Infrared Image Object Detection by Nan Xiao, Xianggong Hong, Zixuan Zheng

“…This paper presents an infrared small object detection algorithm based on YOLOv8n to address challenges like large model size, complex backgrounds, poor small object detection, and scale variations. …”
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Advanced Object Detection in Low-Light Conditions: Enhancements to YOLOv7 Framework by Dewei Zhao, Faming Shao, Sheng Zhang, Li Yang, Heng Zhang, Shaodong Liu, Qiang Liu

“…Object detection in low-light conditions is increasingly relevant across various applications, presenting a challenge for improving accuracy. …”
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IDDNet: Infrared Object Detection Network Based on Multi-Scale Fusion Dehazing by Shizun Sun, Shuo Han, Junwei Xu, Jie Zhao, Ziyu Xu, Lingjie Li, Zhaoming Han, Bo Mo

“…In foggy environments, infrared images suffer from reduced contrast, degraded details, and blurred objects, which impair detection accuracy and real-time performance. …”
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3L-YOLO: A Lightweight Low-Light Object Detection Algorithm by Zhenqi Han, Zhen Yue, Lizhuang Liu

“…Object detection in low-light conditions presents significant challenges due to issues such as weak contrast, high noise, and blurred boundaries. …”
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Automatic detection of foreign object intrusion along railway tracks based on MACENet. by Xichun Chen, Yu Tian, Ming Li, Bin Lv, Shuo Zhang, Zixian Qu, Jianqing Wu, Shiya Cheng

“…Meanwhile, to improve localization robustness, the generalized intersection over union (GIoU) loss function is implemented, offering more reliable detection across various object sizes and shapes. …”
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Small object detection algorithm based on improved YOLOv10 for traffic sign by Yukang Zou, Scarlett Liu

“…Additionally, we integrate an attention-guided bidirectional feature pyramid network (EMA-BiFPN) to enhance feature fusion, further improving the detection accuracy for small objects. The MPDIoU loss function is employed during bounding box regression to optimize precision and recall for irregularly shaped targets. …”
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SDA-YOLO: An Object Detection Method for Peach Fruits in Complex Orchard Environments by Xudong Lin, Dehao Liao, Zhiguo Du, Bin Wen, Zhihui Wu, Xianzhi Tu

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Optimizing RetinaNet anchors using differential evolution for improved object detection by Asaad Mohammed, Hosny M. Ibrahim, Nagwa M. Omar

“…Its success is largely due to the groundbreaking focal loss function, which adeptly addresses the issue of class imbalance prevalent in object detection tasks. …”
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An Efficient Algorithm for Small Livestock Object Detection in Unmanned Aerial Vehicle Imagery by Wenbo Chen, Dongliang Wang, Xiaowei Xie

“…Our approach incorporates a low-level prediction head (P2) to detect small objects from shallow feature maps, while removing a deep-level prediction head (P5) to mitigate the effects of excessive down-sampling. …”
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Real‐time object detection for unmanned vehicles in Bangladesh: Dataset, implementation and evaluation by Muhammad Liakat Ali, Topu Biswas, Shahin Akter, Mohammed Farhan Jawad, Hadaate Ullah

“…Abstract Automated vehicle detection within the advanced application framework of autonomous vehicles significantly enhances road safety compared to human drivers on roads and highways. …”
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Curriculum-Guided Adversarial Learning for Enhanced Robustness in 3D Object Detection by Jinzhe Huang, Yiyuan Xie, Zhuang Chen, Ye Su

“…The pursuit of robust 3D object detection has emerged as a critical focus within the realm of computer vision. …”
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Detection System Design and Implementation for Foreign Objects in Automatic Platform Door Gap by YU Qingguang, WANG Shi, GAO Bonan, CHEN Yuxuan, XIAO Chengbo, LIU Youqi, WANG Yujin, ZHAO Ming, LI Le, CAI Guanzhi

“…Result & Conclusion In system design, a cross-stacking layered sensor installation method is proposed, enabling the redundant detection function of foreign objects in platform door gaps. …”
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The Neurometabolic Function of the Dopamine–Aminotransferase System by Sergey A. Apryatin

“…Background/Objectives: The neurometabolic function is controlled by a complex multi-level physiological system that includes neurochemical, hormonal, immunological, sensory, and metabolic components. …”
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Effect of Transcatheter Arterial Chemoembolization Combined with Radiofrequency Ablation on Liver Function and Immune Function in Patients with Hepatocellular Carcinoma by Yan Zhou, Ying Qian, Weiming Xiong, Naijun Yan, Bing Hu, Zhiyuan Xiong, Weixin He

“…Objectives. To investigate the effects of transcatheter arterial chemoembolization (TACE) combined with radiofrequency ablation (RFA) on liver function and immune function in patients with hepatocellular carcinoma (HCC). …”
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Research on object detection and recognition in remote sensing images based on YOLOv11 by Lu-hao He, Yong-zhang Zhou, Lei Liu, Wei Cao, Jian-hua Ma

“…Abstract This study applies the YOLOv11 model to train and detect ground object targets in high-resolution remote sensing images, aiming to evaluate its potential in enhancing detection accuracy and efficiency. …”
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Autonomous Streaming Space Objects Detection Based on a Remote Optical System by V. S. Baranova, V. A. Saetchnikov, A. A. Spiridonov

“…But the speed of the computing architecture and the functions of small optical systems are rapidly developing thus contribute to the use of a dynamic video stream for detecting and initializing space objects. …”
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YOLO-NeRFSLAM: underwater object detection for the visual NeRF-SLAM by Zhe Wang, Zhibin Yu, Zhibin Yu, Bing Zheng, Bing Zheng

“…Through a Marine Motion Fusion (MMF) strategy—leveraging YOLO to detect known marine organisms and integrating optical flow for pixel-level motion analysis—we effectively screen out all dynamic objects, thus maintaining stable camera pose estimation and pixel-level dense reconstruction even without relying on depth data. …”
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Automotive DNN-Based Object Detection in the Presence of Lens Obstruction and Video Compression by Gabriele Baris, Boda Li, Pak Hung Chan, Carlo Alberto Avizzano, Valentina Donzella

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Advancing Early Detection of Major Depressive Disorder Using Multisite Functional Magnetic Resonance Imaging Data: Comparative Analysis of AI Models by Masab Mansoor, Kashif Ansari

“…ObjectiveThis study aimed to develop and validate ML models using multisite functional magnetic resonance imaging data for the early detection of MDD, compare their performance, and evaluate their clinical applicability. …”
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