Zobrazeno 1 - 10
of 133
pro vyhledávání: '"Hangen He"'
Publikováno v:
Sensors, Vol 15, Iss 11, Pp 29594-29617 (2015)
Road detection is an essential component of field robot navigation systems. Vision sensors play an important role in road detection for their great potential in environmental perception. In this paper, we propose a hierarchical vision sensor-based me
Externí odkaz:
https://doaj.org/article/37da89c8fd38450a994c5af017a07df8
Publikováno v:
Sensors, Vol 14, Iss 5, Pp 9046-9073 (2014)
Curb detection is an essential component of Autonomous Land Vehicles (ALV), especially important for safe driving in urban environments. In this paper, we propose a fusion-based curb detection method through exploiting 3D-Lidar and camera data. More
Externí odkaz:
https://doaj.org/article/6848ca1fbf8b43f4b88fdf59f754b04d
Publikováno v:
Symmetry, Vol 10, Iss 9, p 375 (2018)
Nowadays, video surveillance has become ubiquitous with the quick development of artificial intelligence. Multi-object detection (MOD) is a key step in video surveillance and has been widely studied for a long time. The majority of existing MOD algor
Externí odkaz:
https://doaj.org/article/2cb80c5215744c28a0727ab5f7692555
Publikováno v:
Symmetry, Vol 10, Iss 9, p 370 (2018)
Modelling the multimedia data such as text, images, or videos usually involves the analysis, prediction, or reconstruction of them. The recurrent neural network (RNN) is a powerful machine learning approach to modelling these data in a recursive way.
Externí odkaz:
https://doaj.org/article/96c4580373964c2b97db3843ffb6368b
Publikováno v:
International Journal of Advanced Robotic Systems, Vol 10 (2013)
Unstructured road detection is a key step in an unmanned guided vehicle (UGV) system for road following. However, current vision-based unstructured road detection algorithms are usually affected by continuously changing backgrounds, different road ty
Externí odkaz:
https://doaj.org/article/6c4d6c8a01f64e4ca788a4d5e46060e4
Publikováno v:
IEEE Transactions on Automation Science and Engineering. 15:1448-1458
Object detection is important in car sharing services. Accuracy, efficiency, and low memory consumption are desirable for object detection in car sharing services. This paper presents a network system that satisfies all these requirements. Our approa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf1a9b8b266a6e2782f04aa170492143
https://doi.org/10.1109/tase.2018.2830655
https://doi.org/10.1109/tase.2018.2830655
Publikováno v:
Computer Vision and Image Understanding. 172:77-87
Vision-based player detection and classification are important in sports applications. Accuracy, efficiency, and low memory consumption are desirable for real-time tasks such as intelligent broadcasts and event classification. In this paper, we prese
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1fe7cba60ddd16bf7c067d45a7978594
https://doi.org/10.1016/j.cviu.2018.02.008
https://doi.org/10.1016/j.cviu.2018.02.008
Publikováno v:
Neurocomputing. 245:31-45
Vision-based object detection is essential for a multitude of robotic applications. However, it is also a challenging job due to the diversity of the environments in which such applications are required to operate, and the strict constraints that app
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::65e54a1a7582ff0d484a816cd030e59c
https://doi.org/10.1016/j.neucom.2017.03.050
https://doi.org/10.1016/j.neucom.2017.03.050
Publikováno v:
Mechanical Systems and Signal Processing. 87:118-137
This study proposes a novel integrated local trajectory planning and tracking control (ILTPTC) framework for autonomous vehicles driving along a reference path with obstacles avoidance. For this ILTPTC framework, an efficient state-space sampling-bas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b242d27940fcba79424d6c3043f88bb6
https://doi.org/10.1016/j.ymssp.2015.10.021
https://doi.org/10.1016/j.ymssp.2015.10.021
Publikováno v:
CVPR
Online Multi-Object Tracking (MOT) from videos is a challenging computer vision task which has been extensively studied for decades. Most of the existing MOT algorithms are based on the Tracking-by-Detection (TBD) paradigm combined with popular machi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a8f84cb10aa9d1af7c46ca64164b6c51
https://doi.org/10.1109/cvpr.2019.00141
https://doi.org/10.1109/cvpr.2019.00141