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Perpetual Hope Akwensi
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2020 – today
- 2024
- [j7]Perpetual Hope Akwensi, Ruisheng Wang, Bo Guo:
PReFormer: A memory-efficient transformer for point cloud semantic segmentation. Int. J. Appl. Earth Obs. Geoinformation 128: 103730 (2024) - [i1]Perpetual Hope Akwensi, Akshay Bharadwaj, Ruisheng Wang:
APC2Mesh: Bridging the gap from occluded building fa\c{c}ades to full 3D models. CoRR abs/2404.02391 (2024) - 2023
- [j6]Perpetual Hope Akwensi
, Zhizhong Kang
, Ruisheng Wang:
Hyperspectral image-aided LiDAR point cloud labeling via spatio-spectral feature representation learning. Int. J. Appl. Earth Obs. Geoinformation 120: 103302 (2023) - [c2]Perpetual Hope Akwensi
, Ruisheng Wang:
A Reversible Transformer for LiDAR Point Cloud Semantic Segmentation. CRV 2023: 19-28 - 2022
- [j5]Hui Wang
, Teng Hu
, Zhen Wang
, Zhizhong Kang
, Perpetual Hope Akwensi
, Juntao Yang
:
Reconstruction of Power Pylons From LiDAR Point Clouds Based on Structural Segmentation and Parameter Estimation. IEEE Geosci. Remote. Sens. Lett. 19: 1-5 (2022) - [c1]Perpetual Hope Akwensi
, Ruisheng Wang:
Attention-Based Multi-Scale Graph Convolution for Point Cloud Semantic Segmentation. IGARSS 2022: 7515-7518 - 2021
- [j4]Juntao Yang
, Zhizhong Kang
, Perpetual Hope Akwensi
:
A Label-Constraint Building Roof Detection Method From Airborne LiDAR Point Clouds. IEEE Geosci. Remote. Sens. Lett. 18(8): 1466-1470 (2021) - 2020
- [j3]Perpetual Hope Akwensi
, Zhizhong Kang
, Juntao Yang
:
Fisher Vector Encoding of Supervoxel-Based Features for Airborne LiDAR Data Classification. IEEE Geosci. Remote. Sens. Lett. 17(3): 504-508 (2020) - [j2]Juntao Yang
, Zhizhong Kang
, Sai Cheng, Zhou Yang, Perpetual Hope Akwensi
:
An Individual Tree Segmentation Method Based on Watershed Algorithm and Three-Dimensional Spatial Distribution Analysis From Airborne LiDAR Point Clouds. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 13: 1055-1067 (2020)
2010 – 2019
- 2019
- [j1]Juntao Yang
, Zhizhong Kang
, Perpetual Hope Akwensi
:
A Skeleton-Based Hierarchical Method for Detecting 3-D Pole-Like Objects From Mobile LiDAR Point Clouds. IEEE Geosci. Remote. Sens. Lett. 16(5): 801-805 (2019)
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last updated on 2024-08-28 22:31 CEST by the dblp team
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