Search Results for author: Haoran Su

Found 7 papers, 0 papers with code

Mine yOur owN Anatomy: Revisiting Medical Image Segmentation with Extremely Limited Labels

no code implementations27 Sep 2022 Chenyu You, Weicheng Dai, Fenglin Liu, Yifei Min, Haoran Su, Xiaoran Zhang, Xiaoxiao Li, David A. Clifton, Lawrence Staib, James S. Duncan

Blindly leveraging all pixels in training hence can lead to the data imbalance issues, and cause deteriorated performance; (2) consistency: it remains unclear whether a segmentation model has learned meaningful and yet consistent anatomical features due to the intra-class variations between different anatomical features; and (3) diversity: the intra-slice correlations within the entire dataset have received significantly less attention.

Anatomy Contrastive Learning +4

A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles

no code implementations30 Oct 2021 Haoran Su, Yaofeng Desmond Zhong, Biswadip Dey, Amit Chakraborty

Consequently, the decentralized RL agents learn network-level cooperative traffic signal phase strategies that reduce EMV travel time and the average travel time of non-EMVs in the network.

reinforcement-learning Reinforcement Learning (RL)

EMVLight: A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles

no code implementations12 Sep 2021 Haoran Su, Yaofeng Desmond Zhong, Biswadip Dey, Amit Chakraborty

EMVLight extends Dijkstra's algorithm to efficiently update the optimal route for the EMVs in real time as it travels through the traffic network.

reinforcement-learning Reinforcement Learning (RL)

A Hybrid Queuing Model for Coordinated Vehicle Platooning on Mixed-Autonomy Highways: Training and Validation

no code implementations26 Mar 2021 Haoran Su, Zhengjie Ji, Karl. H. Johansson, Li Jin

Platooning of connected and autonomous vehicles (CAVs) is an emerging technology with a strong potential for throughput improvement and fuel reduction.

Autonomous Vehicles Decision Making

V2I Connectivity-Based Dynamic Queue-Jump Lane for Emergency Vehicles: A Deep Reinforcement Learning Approach

no code implementations1 Aug 2020 Haoran Su, Kejian Shi, Li Jin, Joseph Y. J. Chow

Emergency vehicle (EMV) service is a key function of cities and is exceedingly challenging due to urban traffic congestion.

Blocking

Dynamic Queue-Jump Lane for Emergency Vehicles under Partially Connected Settings: A Multi-Agent Deep Reinforcement Learning Approach

no code implementations2 Mar 2020 Haoran Su, Kejian Shi, Joseph. Y. J. Chow, Li Jin

Based on pairs of neural networks representing actors and critics for agent vehicles, we develop a multi-agent actor-critic deep reinforcement learning algorithm that handles a varying number of vehicles and a random proportion of connected vehicles in the traffic.

Blocking Multi-agent Reinforcement Learning +2

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