Sergio Fernandez Navarro

Dr Sergio Fernandez works as senior expert in lidar technology at Valeo. After pursuing one master's degree in telecommunications engineering and one in computer vision applied robotics, he continued his research career with a PhD in computer vision, while in parallel he started his contact with lidar. Shortly after this period, he joined Valeo within the lidar software algorithm team, where he developed his professional career as an algorithm developer and algorithm architect. Sergio is currently technical lead for SCALA3 lidar and Valeo's senior expert in lidar technology.

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Presentation

Hardware-aware neural network optimization for lidar dense point cloud

In the current work we propose a method to apply generative AI GAN methodology on a hardware-aware NN for lidar data. In order to improve the network semantic segmentation performance, we introduce a GAN network into the segmentation. The adversarial training encourages the model to generalize better by simulating a diverse range of conditions, improving its robustness in real-world applications. This increases the performance with regard to classical real and simulated data based training approaches. Once the NN is trained, we also apply several compression techniques to optimally reduce the latency of the NN for real-time processing of dense point clouds.