The population of space debris in near-Earth space is continuously growing and it represents a serious problem for active satellites and spacecraft.A performant ground-based and space-based network of sensors is necessary for space surveillance and consequently to prevent new collisions and monitoring atmospheric reentry of these objects.This paper
In this work, we study the performance of wide-used keypoints detection and description algorithms: Scale-Invariant Feature Transform Seat Shaft (SIFT), Speeded Up Robust Features (SURF), Oriented FAST and Rotated BRIEF (ORB), Binary Robust Invariant Scalable Keypoints(BRISK), Accelerated KAZE(AKAZE), which were originally developed for images take
Zeliang Wei,1,2 Haibo Wang,3 Guang Xin,1 Zhi Zeng,1 Shiyi Li,1 Yue Ming,1 Xiaoyu Zhang,1 Zhihua Xing,1 Li Li,2 Youping Li,1 Boli Zhang,1,4 Junhua Zhang,4 Hai Niu,1,5 Wen Huang1 1Laboratory of Ethnopharmacology, West China Medical School, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 2Department of Derm