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pro vyhledávání: '"Fei Xiaoxiao"'
Akademický článek
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This paper addresses the problem of cross-season visual place classification (VPC) from a novel perspective of long-term map learning. Our goal is to enable transfer learning efficiently from one season to the next, at a small constant cost, and with
Externí odkaz:
http://arxiv.org/abs/1709.05470
Publikováno v:
ITSC
Vision-based global localization without a prior location estimate is a fundamental task for safe and efficient vehicle navigation in GPS-denied environments. Cross-season localization, in which query and database images involve different seasons is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ae5d385df494784b6c84be6f5027948
https://doi.org/10.1109/itsc.2018.8569966
https://doi.org/10.1109/itsc.2018.8569966
Publikováno v:
2018 57th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE).
In this study, we address the problem of supervised change detection for robotic map learning applications, in which the aim is to train a place-specific change classifier (e.g., support vector machine (SVM)) to predict changes from a robot's view im
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::020a5d966d13ab5afb330e0a5d900cd1
https://doi.org/10.23919/sice.2018.8492631
https://doi.org/10.23919/sice.2018.8492631
Akademický článek
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Publikováno v:
IPIN
Map retrieval, the problem of similarity search over a large collection of 2D pointset maps previously built by mobile robots, is crucial for autonomous navigation in indoor and outdoor environments. Bag-of-words (BoW) methods constitute a popular ap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a53b8000c1d6a3336b9205cea24c634a
https://doi.org/10.1109/ipin.2017.8115884
https://doi.org/10.1109/ipin.2017.8115884
Publikováno v:
MVA
In this study, we explore the use of deep convolutional neural network (DCNN) in visual place classification for robotic mapping and localization. An open question is how to partition the robot's workspace into places so as to maximize the performanc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::26132557734ef299fb5eac796d79758b
https://doi.org/10.23919/mva.2017.7986802
https://doi.org/10.23919/mva.2017.7986802