Muhammad Rabani Mohd Romlay

LiDAR point cloud data serves as an machine vision alternative other than image. Its advantages when compared to image and video includes depth estimation and distance measruement. Low-density LiDAR point cloud data can be used to achieve navigation, obstacle detection and obstacle avoidance for mobile robots. autonomous vehicle and drones. In this metadata, we scanned over 1200 objects and classified it into 4 groups of object namely, human, cars, motorcyclist.

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[1] Muhammad Rabani Mohd Romlay, Azhar Mohd Ibrahim, Siti Fauziah Toha, "LiDAR Point Cloud Object Classification", IEEE Dataport, 2021. [Online]. Available: http://dx.doi.org/10.21227/f61n-5e90. Accessed: Apr. 22, 2024.
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doi = {10.21227/f61n-5e90},
url = {http://dx.doi.org/10.21227/f61n-5e90},
author = {Muhammad Rabani Mohd Romlay; Azhar Mohd Ibrahim; Siti Fauziah Toha },
publisher = {IEEE Dataport},
title = {LiDAR Point Cloud Object Classification},
year = {2021} }
TY - DATA
T1 - LiDAR Point Cloud Object Classification
AU - Muhammad Rabani Mohd Romlay; Azhar Mohd Ibrahim; Siti Fauziah Toha
PY - 2021
PB - IEEE Dataport
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Muhammad Rabani Mohd Romlay, Azhar Mohd Ibrahim, Siti Fauziah Toha. (2021). LiDAR Point Cloud Object Classification. IEEE Dataport. http://dx.doi.org/10.21227/f61n-5e90
Muhammad Rabani Mohd Romlay, Azhar Mohd Ibrahim, Siti Fauziah Toha, 2021. LiDAR Point Cloud Object Classification. Available at: http://dx.doi.org/10.21227/f61n-5e90.
Muhammad Rabani Mohd Romlay, Azhar Mohd Ibrahim, Siti Fauziah Toha. (2021). "LiDAR Point Cloud Object Classification." Web.
1. Muhammad Rabani Mohd Romlay, Azhar Mohd Ibrahim, Siti Fauziah Toha. LiDAR Point Cloud Object Classification [Internet]. IEEE Dataport; 2021. Available from : http://dx.doi.org/10.21227/f61n-5e90
Muhammad Rabani Mohd Romlay, Azhar Mohd Ibrahim, Siti Fauziah Toha. "LiDAR Point Cloud Object Classification." doi: 10.21227/f61n-5e90