Search Results for author: Li Feng

Found 5 papers, 1 papers with code

Learning Optimal K-space Acquisition and Reconstruction using Physics-Informed Neural Networks

no code implementations5 Apr 2022 Wei Peng, Li Feng, Guoying Zhao, Fang Liu

While most of these methods focus on designing novel reconstruction networks or new training strategies for a given undersampling pattern, e. g., Cartesian undersampling or Non-Cartesian sampling, to date, there is limited research aiming to learn and optimize k-space sampling strategies using deep neural networks.

Image Reconstruction

Interaction Detection Between Vehicles and Vulnerable Road Users: A Deep Generative Approach with Attention

no code implementations9 May 2021 Hao Cheng, Li Feng, Hailong Liu, Takatsugu Hirayama, Hiroshi Murase, Monika Sester

Intersections where vehicles are permitted to turn and interact with vulnerable road users (VRUs) like pedestrians and cyclists are among some of the most challenging locations for automated and accurate recognition of road users' behavior.

Frame Optical Flow Estimation +1

Few-Shot Meta-Learning on Point Cloud for Semantic Segmentation

no code implementations7 Apr 2021 Xudong Li, Li Feng, Lei LI, Chen Wang

With a good understanding of environmental information, construction robots can work better.

Autonomous Driving Meta-Learning +1

SANTIS: Sampling-Augmented Neural neTwork with Incoherent Structure for MR image reconstruction

no code implementations8 Dec 2018 Fang Liu, Lihua Chen, Richard Kijowski, Li Feng

The undersampled images are generated by a fixed undersampling pattern in the training, and the trained network is then applied to reconstruct new images acquired with the same pattern in the inference.

Image Reconstruction

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