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Deep Reinforcement Learning framework for Autonomous Driving

Electronic Imaging, 2017-01, Vol.29 (19), p.70-76

2017

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Real-time face & eye tracking and blink detection using event cameras

Neural networks, 2021-09, Vol.141, p.87-97

2021

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Coronary Artery Centerline Tracking with the Morphological Skeleton Loss

2022 IEEE International Conference on Image Processing (ICIP), 2022, p.2741-2745

2022

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End-to-End Race Driving with Deep Reinforcement Learning

2018 IEEE International Conference on Robotics and Automation (ICRA), 2018, p.2070-2075

2018

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End-to-End Driving in a Realistic Racing Game with Deep Reinforcement Learning

2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2017, p.474-475

2017

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Detecting Stable Keypoints from Events through Image Gradient Prediction

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2021, p.1387-1394

2021

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IEEE_Xplore

Single-cell RNA-sequencing of PBMCs from SAVI patients reveals disease-associated monocytes with elevated integrated stress response

Cell reports. Medicine, 2023-12, Vol.4 (12), p.101333-101333, Article 101333

2023

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Brainstem responses can predict death and delirium in sedated patients in intensive care unit

Critical care medicine, 2011-08, Vol.39 (8), p.1960-1967

2011

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Performance of the polarization leakage correction in the PILOT data

Deep Reinforcement Learning framework for Autonomous Driving

Real-time face & eye tracking and blink detection using event cameras

Coronary Artery Centerline Tracking with the Morphological Skeleton Loss

End-to-End Race Driving with Deep Reinforcement Learning

End-to-End Driving in a Realistic Racing Game with Deep Reinforcement Learning

Detecting Stable Keypoints from Events through Image Gradient Prediction

Single-cell RNA-sequencing of PBMCs from SAVI patients reveals disease-associated monocytes with elevated integrated stress response

Wide diversity of PAX5 alterations in B-ALL: a Groupe Francophone de Cytogénétique Hématologique study

Brainstem responses can predict death and delirium in sedated patients in intensive care unit

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