most citedTowards Adaptive Semantic Segmentation by Progressive Feature Refinement

3 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2020

Robust Two-Stream Multi-Feature Network for Driver Drowsiness Detection

Qi Shen, Shengjie Zhao, Rongqing Zhang +1

Drowsiness driving is a major cause of traffic accidents and thus numerous previous researches have focused on driver drowsiness detection. Many drive relevant factors have been ta…

cs.CV20203 cited

Towards Adaptive Semantic Segmentation by Progressive Feature Refinement

Bin Zhang, Shengjie Zhao, Rongqing Zhang

As one of the fundamental tasks in computer vision, semantic segmentation plays an important role in real world applications. Although numerous deep learning models have made notab…

eess.SP2020

Learning-Based Massive Beamforming

Siyuan Lu, Shengjie Zhao, Qingjiang Shi

Developing resource allocation algorithms with strong real-time and high efficiency has been an imperative topic in wireless networks. Conventional optimization-based iterative res…

eess.IV2019

Spatial Sparse subspace clustering for Compressive Spectral imaging

Jianchen Zhu, Tong Zhang, Shengjie Zhao +3

This paper aims at developing a clustering approach with spectral images directly from CASSI compressive measurements. The proposed clustering method first assumes that compressed…

cs.IT2019

Greedy Signal Space Recovery Algorithm with Overcomplete Dictionaries in Compressive Sensing

Jianchen Zhu, Shengjie Zhao, Qingjiang Shi +1

Compressive Sensing (CS) is a new paradigm for the efficient acquisition of signals that have sparse representation in a certain domain. Traditionally, CS has provided numerous met…