EMDS-7: Environmental microorganism image dataset seventh version for multiple object detection evaluation [PDF]
Frontiers in Microbiology, 2023 Nowadays, the detection of environmental microorganism indicators is essential for us to assess the degree of pollution, but the traditional detection methods consume a lot of manpower and material resources.
Hechen Yang +15 more
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Dynamic Multi-LiDAR Based Multiple Object Detection and Tracking [PDF]
Sensors, 2019 Environmental perception plays an essential role in autonomous driving tasks and demands robustness in cluttered dynamic environments such as complex urban scenarios.
Muhammad Sualeh, Gon-Woo Kim
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Multiple Object Detection Based on Clustering and Deep Learning Methods [PDF]
Sensors, 2020 Multiple object detection is challenging yet crucial in computer vision. In This study, owing to the negative effect of noise on multiple object detection, two clustering algorithms are used on both underwater sonar images and three-dimensional point ...
Huu Thu Nguyen +3 more
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Multiple spatial residual network for object detection
Complex & Intelligent Systems, 2022 Many residual network-based methods have been proposed to perform object detection. However, most of them may lead to overfitting or cannot perform well in small object detection and alleviate the problem of overfitting.
Yongsheng Dong +3 more
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3D Object Detection Using Multiple-Frame Proposal Features Fusion
Sensors, 2023 Object detection is important in many applications, such as autonomous driving. While 2D images lack depth information and are sensitive to environmental conditions, 3D point clouds can provide accurate depth information and a more descriptive ...
Minyuan Huang, Henry Leung, Ming Hou
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M3OT: A Multi-Drone Multi-Modality dataset for Multi-Object Tracking [PDF]
Scientific DataWe provide a dataset for object detection and tracking in aerial imagery, namely “M3OT”. M3OT is a multi-modality vehicle detection and tracking dataset acquired by two Unmanned Aerial Vehicles (UAVs) in a high-altitude region, consisting both RGB and ...
Zhihao Nie +5 more
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Multiple Instance Active Learning for Object Detection [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Despite the substantial progress of active learning for image recognition, there still lacks an instance-level active learning method specified for object detection. In this paper, we propose Multiple Instance Active Object Detection (MI-AOD), to select the most informative images for detector training by observing instance-level uncertainty.
Yuan, Tianning +6 more
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Multiple Object Tracking Using Edge Multi-Channel Gradient Model With ORB Feature
IEEE Access, 2021 Multiple object tracking based on tracking-by-detection is the most common method used in addressing illumination change and occlusion problems. In this paper, we present a tracking algorithm based on Edge Multi-channel Gradient Model.
Jieyu Chen +5 more
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Evaluation of 3D Vulnerable Objects’ Detection Using a Multi-Sensors System for Autonomous Vehicles
Sensors, 2022 One of the primary tasks undertaken by autonomous vehicles (AVs) is object detection, which comes ahead of object tracking, trajectory estimation, and collision avoidance.
Esraa Khatab +2 more
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A novel real-time multiple objects detection and tracking framework for different challenges
Alexandria Engineering Journal, 2022 Recently, there was a lot of researches on real-time detection and tracking algorithms, as the frequent use of surveillance cameras and the expansion of its applications, especially in security and surveillance. However, many challenges have emerged that
Nuha H. Abdulghafoor, Hadeel N. Abdullah
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