activity
20192024
most citedFinding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs

11 citations · 43 across the 18 of their papers we have counts for

collaborators
Showing 2022Show all

6 papers · 1 filter

cs.RO2022

Recognition and Prediction of Surgical Gestures and Trajectories Using Transformer Models in Robot-Assisted Surgery

Chang Shi, Yi Zheng, Ann Majewicz Fey

Surgical activity recognition and prediction can help provide important context in many Robot-Assisted Surgery (RAS) applications, for example, surgical progress monitoring and est…

eess.SP2022★ 9 cited

A Random Forest and Current Fault Texture Feature-Based Method for Current Sensor Fault Diagnosis in Three-Phase PWM VSR

Lei Kou, Xiao-dong Gong, Yi Zheng +4

Three-phase PWM voltage-source rectifier (VSR) systems have been widely used in various energy conversion systems, where current sensors are the key component for state monitoring…

cs.IR2022

Improving Micro-video Recommendation by Controlling Position Bias

Yisong Yu, Beihong Jin, Jiageng Song +3

As the micro-video apps become popular, the numbers of micro-videos and users increase rapidly, which highlights the importance of micro-video recommendation. Although the micro-vi…

physics.optics2022★ 6 cited

Toward practical weak measurement wavefront sensing: spatial resolution and achromatism

Yi Zheng, Mu Yang, Zheng-Hao Liu +3

The weak measurement wavefront sensor detects the phase gradient of light like the Shack-Hartmann sensor does. However, the use of one thin birefringent crystal to displace light b…

cs.IR2022

Improving Micro-video Recommendation via Contrastive Multiple Interests

Beibei Li, Beihong Jin, Jiageng Song +3

With the rapid increase of micro-video creators and viewers, how to make personalized recommendations from a large number of candidates to viewers begins to attract more and more a…

cs.CV2022

Multi-Level Attention for Unsupervised Person Re-Identification

Yi Zheng

The attention mechanism is widely used in deep learning because of its excellent performance in neural networks without introducing additional information. However, in unsupervised…