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Chen Feng

5 papers here

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 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.LG1
same name
  • Chen Feng — 14 papers
  • Chen Feng — 5 papers
  • Chen Feng — 5 papers, h 11
  • Chen Feng — 5 papers, h 14
  • Chen Feng — 3 papers
  • Chen Feng — 2 papers

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
20182022
most citedAn Empirical Study of Low Precision Quantization for TinyML

12 citations · 17 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2019★ 5 cited

Low-Power Computer Vision: Status, Challenges, Opportunities

Sergei Alyamkin, Matthew Ardi, Alexander C. Berg +41

Computer vision has achieved impressive progress in recent years. Meanwhile, mobile phones have become the primary computing platforms for millions of people. In addition to mobile…

cs.CV2019

Low Power Inference for On-Device Visual Recognition with a Quantization-Friendly Solution

Chen Feng, Tao Sheng, Zhiyu Liang +9

The IEEE Low-Power Image Recognition Challenge (LPIRC) is an annual competition started in 2015 that encourages joint hardware and software solutions for computer vision systems wi…

cs.CV2018

2018 Low-Power Image Recognition Challenge

Sergei Alyamkin, Matthew Ardi, Achille Brighton +38

The Low-Power Image Recognition Challenge (LPIRC, https://rebootingcomputing.ieee.org/lpirc) is an annual competition started in 2015. The competition identifies the best technolog…

cs.CV2018

A Quantization-Friendly Separable Convolution for MobileNets

Tao Sheng, Chen Feng, Shaojie Zhuo +3

As deep learning (DL) is being rapidly pushed to edge computing, researchers invented various ways to make inference computation more efficient on mobile/IoT devices, such as netwo…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.