activity
20192022
most citedReliability Validation of Learning Enabled Vehicle Tracking

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2022

CSFlow: Learning Optical Flow via Cross Strip Correlation for Autonomous Driving

Hao Shi, Yifan Zhou, Kailun Yang +2

Optical flow estimation is an essential task in self-driving systems, which helps autonomous vehicles perceive temporal continuity information of surrounding scenes. The calculatio…

cs.CV2021

Friends and Foes in Learning from Noisy Labels

Yifan Zhou, Yifan Ge, Jianxin Wu

Learning from examples with noisy labels has attracted increasing attention recently. But, this paper will show that the commonly used CIFAR-based datasets and the accuracy evaluat…

cs.CV20202 cited

Reliability Validation of Learning Enabled Vehicle Tracking

Youcheng Sun, Yifan Zhou, Simon Maskell +2

This paper studies the reliability of a real-world learning-enabled system, which conducts dynamic vehicle tracking based on a high-resolution wide-area motion imagery input. The s…

cs.CV2019

Detecting and Tracking Small Moving Objects in Wide Area Motion Imagery (WAMI) Using Convolutional Neural Networks (CNNs)

Yifan Zhou, Simon Maskell

This paper proposes an approach to detect moving objects in Wide Area Motion Imagery (WAMI), in which the objects are both small and well separated. Identifying the objects only us…

eess.IV2019

Robust and Accurate Global Motion Estimation Using the Student-t Distribution

Yifan Zhou, Simon Maskell

Pixel-based Global Motion Estimation (GME) has always struggled to simultaneously reject outliers, avoid local minima and run quickly. There are many robust cost functions that per…