Hong Yang

Automotive Engineering · with Ma · 2020

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Hong Yang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Mariusz Bojarski
  2. Anna Petrovskaya

Papers from Hong Yang's perspective

Ordered by how strongly the researchers Hong Yang trusts endorse each paper. Same corpus, a different order for every researcher.

  1. End to End Learning for Self-Driving Cars
  2. ALVINN, an autonomous land vehicle in a neural network
  3. DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving
  4. Computer vision in automated parking systems: Design, implementation and challenges
  5. Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving
  6. Model based vehicle detection and tracking for autonomous urban driving
  7. Street-view change detection with deconvolutional networks (Autonomous Robots)
  8. Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car
  9. Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks (Transport reviews)
  10. Millimeter-Wave Vehicular Communication to Support Massive Automotive Sensing (IEEE Communications Magazine)

Their papers