Searched for: author%3A%22Zheng%2C+M.%22
(1 - 5 of 5)
document
Zheng, M. (author), Wu, Huayi (author), Li, Y. (author)
It is fundamental for 3D city maps to efficiently classify objects of point clouds in urban scenes. However, it is still a large challenge to obtain massive training samples for point clouds and to sustain the huge training burden. To overcome it, a knowledge-based approach is proposed. The knowledge-based approach can explore discriminating...
journal article 2019
document
Chen, Y. (author), Gao, W. (author), Widyaningrum, E. (author), Zheng, M. (author), Zhou, K. (author)
Semantic segmentation, especially for buildings, from the very high resolution (VHR) airborne images is an important task in urban mapping applications. Nowadays, the deep learning has significantly improved and applied in computer vision applications. Fully Convolutional Networks (FCN) is one of the tops voted method due to their good...
journal article 2018
document
Zheng, M. (author), Lemmens, M.J.P.M. (author), van Oosterom, P.J.M. (author)
This paper presents our work on automated classification of Mobile Laser Scanning (MLS) point clouds of urban scenes with features derived from cylinders around points of consideration. The core of our method consists of spanning up a cylinder around points and deriving features, such as reflectance, height difference, from the points present...
conference paper 2018
document
Zheng, M. (author), Lemmens, M.J.P.M. (author), van Oosterom, P.J.M. (author)
This paper focusses on the feasibility of classifiers, developed for classifying multispectral images, for assigning classes to point clouds of urban scenes. The motivation of our research is that dense point clouds require fast classification methods to extract meaningful information within a reasonable amount of time and multispectral...
conference paper 2017
document
Zheng, M. (author), Lemmens, M.J.P.M. (author), van Oosterom, P.J.M. (author)
The demand for 3D maps of cities and road networks is steadily growing and mobile laser scanning (MLS) systems are often the preferred geo-data acquisition method for capturing such scenes. Because MLS systems are mounted on cars or vans they can acquire billions of points of road scenes within a few hours of survey. Manual processing of...
conference paper 2017
Searched for: author%3A%22Zheng%2C+M.%22
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