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20212025
most citedCCSPNet-Joint: Efficient Joint Training Method for Traffic Sign Detection Under Extreme Conditions

7 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.ET2025

Protonic Nickelate Device Networks for Spatiotemporal Neuromorphic Computing

Yue Zhou, Shaan Shah, Tamal Dey +10

Computation in biological neural circuits arises from the interplay of nonlinear temporal responses and spatially distributed dynamic network interactions. Replicating this richnes…

cond-mat.mtrl-sci2025

Multi-value Probabilistic Computing with current-controlled Skyrmion Diffusion

Thomas B. Winkler, Yuean Zhou, Grischa Beneke +6

Magnetic systems are highly promising for implementing probabilistic computing paradigms because of the fitting energy scales and conspicuous non-linearities. While conventional bi…

cs.CV2023★ 7 cited

CCSPNet-Joint: Efficient Joint Training Method for Traffic Sign Detection Under Extreme Conditions

Haoqin Hong, Yue Zhou, Xiangyu Shu +1

Traffic sign detection is an important research direction in intelligent driving. Unfortunately, existing methods often overlook extreme conditions such as fog, rain, and motion bl…

cs.CV2022

Network Pruning via Feature Shift Minimization

Yuanzhi Duan, Yue Zhou, Peng He +3

Channel pruning is widely used to reduce the complexity of deep network models. Recent pruning methods usually identify which parts of the network to discard by proposing a channel…

cs.LG2021

Network Compression via Central Filter

Yuanzhi Duan, Xiaofang Hu, Yue Zhou +2

Neural network pruning has remarkable performance for reducing the complexity of deep network models. Recent network pruning methods usually focused on removing unimportant or redu…