activity
20182020
most citedCloud2Edge Elastic AI Framework for Prototyping and Deployment of AI Inference Engines in Autonomous Vehicles

20 citations · 35 across the 6 of their papers we have counts for

collaborators

8 papers

cs.SE202020 cited

Cloud2Edge Elastic AI Framework for Prototyping and Deployment of AI Inference Engines in Autonomous Vehicles

Sorin Grigorescu, Tiberiu Cocias, Bogdan Trasnea +3

Self-driving cars and autonomous vehicles are revolutionizing the automotive sector, shaping the future of mobility altogether. Although the integration of novel technologies such…

cs.CV2020

GFPNet: A Deep Network for Learning Shape Completion in Generic Fitted Primitives

Tiberiu Cocias, Alexandru Razvant, Sorin Grigorescu

In this paper, we propose an object reconstruction apparatus that uses the so-called Generic Primitives (GP) to complete shapes. A GP is a 3D point cloud depicting a generalized sh…

cs.LG2019

A Survey of Deep Learning Techniques for Autonomous Driving

Sorin Grigorescu, Bogdan Trasnea, Tiberiu Cocias +1

The last decade witnessed increasingly rapid progress in self-driving vehicle technology, mainly backed up by advances in the area of deep learning and artificial intelligence. The…

cs.AI2019

AIBA: An AI Model for Behavior Arbitration in Autonomous Driving

Bogdan Trasnea, Claudiu Pozna, Sorin Grigorescu

Driving in dynamically changing traffic is a highly challenging task for autonomous vehicles, especially in crowded urban roadways. The Artificial Intelligence (AI) system of a dri…

cs.RO2019

NeuroTrajectory: A Neuroevolutionary Approach to Local State Trajectory Learning for Autonomous Vehicles

Sorin Grigorescu, Bogdan Trasnea, Liviu Marina +2

Autonomous vehicles are controlled today either based on sequences of decoupled perception-planning-action operations, either based on End2End or Deep Reinforcement Learning (DRL)…

cs.CV2019

Deep Grid Net (DGN): A Deep Learning System for Real-Time Driving Context Understanding

Liviu Marina, Bogdan Trasnea, Cocias Tiberiu +3

Grid maps obtained from fused sensory information are nowadays among the most popular approaches for motion planning for autonomous driving cars. In this paper, we introduce Deep G…