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Bo Wu

Researcher at Hong Kong Polytechnic University

Publications -  125
Citations -  1967

Bo Wu is an academic researcher from Hong Kong Polytechnic University. The author has contributed to research in topics: Photogrammetry & Point cloud. The author has an hindex of 21, co-authored 119 publications receiving 1367 citations. Previous affiliations of Bo Wu include Ohio State University & University of Hong Kong.

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An adaptive surface filter for airborne laser scanning point clouds by means of regularization and bending energy

TL;DR: An adaptive surface filter (ASF) is proposed for the classification of ALS point clouds based on the principle that the threshold should vary in accordance to the terrain smoothness, which quantitatively depicts the local terrain structure to self-adapt the filter threshold automatically.
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Automatic detection of individual oil palm trees from UAV images using HOG features and an SVM classifier

TL;DR: In this paper, the number of oil palm trees in a plantation area is important to predict the yield of palm oil, manage the yield, and manage the management of the plantations.
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Robust point cloud classification based on multi-level semantic relationships for urban scenes

TL;DR: A point cloud classification method based on multi-level semantic relationships, including point–homogeneity, supervoxel–adjacency and class–knowledge constraints, which is more versatile and incrementally propagate the classification cues from individual points to the object level and formulate them as a graphical model is proposed.
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LEGION-Based Automatic Road Extraction From Satellite Imagery

TL;DR: An automatic method for road extraction from satellite imagery using locally excitatory globally inhibitory oscillator networks (LEGION) and a comparison with other methods shows that the proposed method produces very competitive extraction results.
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Integration of Chang'E-2 imagery and LRO laser altimeter data with a combined block adjustment for precision lunar topographic modeling

TL;DR: In this article, a combined block adjustment approach was proposed to integrate multiple strips of the Chinese Chang'E-2 imagery and NASA's Lunar Reconnaissance Orbiter (LRO) Laser Altimeter (LOLA) data for precision topographic modeling.