Zobrazeno 1 - 10
of 121
pro vyhledávání: '"Random Ferns"'
Autor:
Sangwon Kim, Byoung Chul Ko
Publikováno v:
IEEE Access, Vol 8, Pp 8533-8542 (2020)
Randomized sampling-based ensemble learning is emerging as a new alternative to deep neural networks (DNNs) because it supports diversity and locality and does not require backpropagation in the learning process. By connecting randomized weak classif
Externí odkaz:
https://doaj.org/article/555d2f99acc2496396ed7b4394ca89ee
Publikováno v:
IEEE Access, Vol 6, Pp 19396-19406 (2018)
This paper presents a lightweight statistical learning framework potentially suitable for low-cost event-based vision systems, where visual information is captured by a dynamic vision sensor (DVS) and represented as an asynchronous stream of pixel ad
Externí odkaz:
https://doaj.org/article/5c6584ce90a8465db22b57429190df95
Publikováno v:
IEEE Access, Vol 6, Pp 48675-48687 (2018)
Multi-pedestrian tracking (MPT) on the road is closely related to a reduction in the possibility of pedestrian-vehicle collisions when using advanced driver assistance systems. Therefore, this paper focuses on MPT on real roads using a moving camera.
Externí odkaz:
https://doaj.org/article/c00e51fab54d465a934a59d432271612
Autor:
Wei He, Jinguo Huang, Tengxiao Wang, Yingcheng Lin, Junxian He, Xichuan Zhou, Ping Li, Ying Wang, Nanjian Wu, Cong Shi
Publikováno v:
Sensors, Vol 20, Iss 17, p 4715 (2020)
This paper proposes a high-speed low-cost VLSI system capable of on-chip online learning for classifying address-event representation (AER) streams from dynamic vision sensor (DVS) retina chips. The proposed system executes a lightweight statistic al
Externí odkaz:
https://doaj.org/article/9e88b6b0aaa54e93a945f5d2f35e7d07
Publikováno v:
Sensors, Vol 18, Iss 6, p 1937 (2018)
In this paper, we carry out researches on randomized local binary features. Randomized local binary features have been used in many methods like RandomForests, RandomFerns, BRIEF, ORB and AKAZE to matching keypoints. However, in those existing method
Externí odkaz:
https://doaj.org/article/d55c1b83bc314fc0911f87d27d882492
Akademický článek
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Akademický článek
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ÐÐ°Ð½Ð½Ð°Ñ ÑабоÑа поÑвÑÑена иÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¸ ÑеализаÑии модиÑикаÑий Deep Forest длÑ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35661c1ca6b4b3d6b7f65d387da5f1c0
Autor:
Tengxiao Wang, Nanjian Wu, Xichuan Zhou, Junxian He, Ping Li, Cong Shi, Wei He, Ying Wang, Yingcheng Lin, Jinguo Huang
Publikováno v:
Sensors, Vol 20, Iss 4715, p 4715 (2020)
Sensors (Basel, Switzerland)
Sensors
Volume 20
Issue 17
Sensors (Basel, Switzerland)
Sensors
Volume 20
Issue 17
This paper proposes a high-speed low-cost VLSI system capable of on-chip online learning for classifying address-event representation (AER) streams from dynamic vision sensor (DVS) retina chips. The proposed system executes a lightweight statistic al
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0aa357cc9db69d3b0ad0bf303142ae4
https://www.mdpi.com/1424-8220/20/17/4715
https://www.mdpi.com/1424-8220/20/17/4715