5 citations · 5 across the 1 of their papers we have counts for
2 papers
eess.IV2019★ 5 cited
Unsupervised Neural Sensor Models for Synthetic LiDAR Data Augmentation
Ahmad El Sallab, Ibrahim Sobh, Mohamed Zahran +1
Data scarcity is a bottleneck to machine learning-based perception modules, usually tackled by augmenting real data with synthetic data from simulators. Realistic models of the veh…
eess.IV2019
End-to-end sensor modeling for LiDAR Point Cloud
Khaled Elmadawi, Moemen Abdelrazek, Mohamed Elsobky +2
Advanced sensors are a key to enable self-driving cars technology. Laser scanner sensors (LiDAR, Light Detection And Ranging) became a fundamental choice due to its long-range and…