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Wenyu Sun

4 papers hereh-index 346 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
same name
  • Wenyu Sun — 2 papers, h 4
  • Wenyu Sun — 2 papers, h 14
  • Wenyu Sun — 1 paper, h 20
  • Wenyu Sun — 1 paper, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202023
most citedLayer Pruning via Fusible Residual Convolutional Block for Deep Neural Networks

14 citations · 16 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023

Razor SNN: Efficient Spiking Neural Network with Temporal Embeddings

Yuan Zhang, Jian Cao, Ling Zhang +3

The event streams generated by dynamic vision sensors (DVS) are sparse and non-uniform in the spatial domain, while still dense and redundant in the temporal domain. Although spiki…

cs.CV2021★ 2 cited

AdaPruner: Adaptive Channel Pruning and Effective Weights Inheritance

Xiangcheng Liu, Jian Cao, Hongyi Yao +2

Channel pruning is one of the major compression approaches for deep neural networks. While previous pruning methods have mostly focused on identifying unimportant channels, channel…

cs.CV2020

An Once-for-All Budgeted Pruning Framework for ConvNets Considering Input Resolution

Wenyu Sun, Jian Cao, Pengtao Xu +2

We propose an efficient once-for-all budgeted pruning framework (OFARPruning) to find many compact network structures close to winner tickets in the early training stage considerin…

cs.CV2020★ 14 cited

Layer Pruning via Fusible Residual Convolutional Block for Deep Neural Networks

Pengtao Xu, Jian Cao, Fanhua Shang +2

In order to deploy deep convolutional neural networks (CNNs) on resource-limited devices, many model pruning methods for filters and weights have been developed, while only a few t…

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