A Trail Detection Using Convolutional Neural Network View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017-10-14

AUTHORS

Jeonghyeok Kim , Heezin Lee , Sanggil Kang

ABSTRACT

Small-footprint airborne LiDAR scanning systems are effective in modelling forest structures and can also improve trail detection. We propose a trail detection method through a machine learning method from the LiDAR points. To do that, we analyze features for detecting a trail, digitize each feature and combine the results to distinguish between trail and non-trail areas. Our proposed method shows the feasibility of trail detection by using airborne LiDAR points gathered in dense mixed forest. More... »

PAGES

275-279

Book

TITLE

Proceedings of the 7th International Conference on Emerging Databases

ISBN

978-981-10-6519-4
978-981-10-6520-0

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-981-10-6520-0_30

DOI

http://dx.doi.org/10.1007/978-981-10-6520-0_30

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1092210518


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