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pro vyhledávání: '"Duan, Kaiwen"'
There are two mainstreams for object detection: top-down and bottom-up. The state-of-the-art approaches mostly belong to the first category. In this paper, we demonstrate that the bottom-up approaches are as competitive as the top-down and enjoy high
Externí odkaz:
http://arxiv.org/abs/2204.08394
Publikováno v:
In Applied Energy 1 November 2024 373
Publikováno v:
In Applied Energy 1 June 2024 363
Object detection, instance segmentation, and pose estimation are popular visual recognition tasks which require localizing the object by internal or boundary landmarks. This paper summarizes these tasks as location-sensitive visual recognition and pr
Externí odkaz:
http://arxiv.org/abs/2104.04899
The goal of object detection is to determine the class and location of objects in an image. This paper proposes a novel anchor-free, two-stage framework which first extracts a number of object proposals by finding potential corner keypoint combinatio
Externí odkaz:
http://arxiv.org/abs/2007.13816
In object detection, keypoint-based approaches often suffer a large number of incorrect object bounding boxes, arguably due to the lack of an additional look into the cropped regions. This paper presents an efficient solution which explores the visua
Externí odkaz:
http://arxiv.org/abs/1904.08189
Akademický článek
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Autor:
Du, Dawei, Qi, Yuankai, Yu, Hongyang, Yang, Yifan, Duan, Kaiwen, Li, Guorong, Zhang, Weigang, Huang, Qingming, Tian, Qi
With the advantage of high mobility, Unmanned Aerial Vehicles (UAVs) are used to fuel numerous important applications in computer vision, delivering more efficiency and convenience than surveillance cameras with fixed camera angle, scale and view. Ho
Externí odkaz:
http://arxiv.org/abs/1804.00518
Publikováno v:
In International Journal of Heat and Mass Transfer 1 December 2022 198
Akademický článek
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