Šį pirmadienį kovo 31 d. 13 val. 203 kab. (Akademijos g. 4) DMSTI seminare parengtą disertaciją pristatys DMSTI doktorantas
Shubham Juneja „Investigation of Pre-training in Imitation Learning Based Autonomous Driving“
[vadovas: prof. dr. Virginijus Marcinkevičius]
Summary: Autonomous vehicles promise transformative changes in transportation, with SLAM-based methods enabling map-based navigation and learning-based approaches leveraging neural networks for data-driven decisions. While SLAM provides map-based navigation, learning-based methods leverage neural networks for data-driven decisions. This study centers on imitation learning within the learning-based paradigm, addressing its limitation, co-variate shifts. The aim is to develop autonomous navigation systems using deep learning and imitation learning, emphasizing pre-training techniques. This research starts off with reviewing state-of-the-art imitation learning methods and pointing out how pre-training in autonomous driving is under-explored. Majority approaches in this area of research choose visual encoders pre-trained on the task of ImageNet classification, rather than searching for better alternative approaches. Therefore, the study proposes application of pre-training methods novel to the task of end-to-end autonomous driving. It then evaluates these methods against baseline approaches to demonstrate enhanced performance.
Maloniai kviečiame dalyvauti! (negalintiems atvykti 'gyvai': https://bit.ly/DMSTI_2025-03-31 )