A Review on Deep Learning Techniques for 3D Sensed Data Classification
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Title
A Review on Deep Learning Techniques for 3D Sensed Data Classification
Authors
Keywords
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Journal
Remote Sensing
Volume 11, Issue 12, Pages 1499
Publisher
MDPI AG
Online
2019-06-25
DOI
10.3390/rs11121499
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- (2017) Michael M. Bronstein et al. IEEE SIGNAL PROCESSING MAGAZINE
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- (2017) Vijay Badrinarayanan et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
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- (2016) Li Yi et al. ACM TRANSACTIONS ON GRAPHICS
- TerraMobilita/iQmulus urban point cloud analysis benchmark
- (2015) Bruno Vallet et al. COMPUTERS & GRAPHICS-UK
- ViDRILO: The Visual and Depth Robot Indoor Localization with Objects information dataset
- (2015) Jesus Martínez-Gómez et al. INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
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- (2013) Ahmad Aijazi et al. Remote Sensing
- Enhanced Computer Vision With Microsoft Kinect Sensor: A Review
- (2013) Jungong Han et al. IEEE Transactions on Cybernetics
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- (2010) Andrew Adams et al. COMPUTER GRAPHICS FORUM
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- (2008) F. Scarselli et al. IEEE TRANSACTIONS ON NEURAL NETWORKS
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