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researcher

Jun Chen

15 papers here

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

author position
  • first author1
  • middle author3
  • last author10

Across the 14 of 15 papers where every author was matched, so the position is known.

fields
  • cs.CV7
  • cs.IT5
  • eess.IV2
  • stat.ME1
ORCID 0000-0002-8084-9332
same name
  • Jun Chen — 37 papers, h 27
  • Jun Chen — 26 papers, h 20
  • Jun Chen — 22 papers, h 14
  • Jun Chen — 20 papers, h 11
  • Jun Chen — 18 papers, h 13
  • Jun Chen — 18 papers, h 13

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
20182025
most citedGridDehazeNet: Attention-Based Multi-Scale Network for Image Dehazing

133 citations · 185 across the 15 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

cs.IT2018★ 3 cited

Successive Wyner-Ziv Coding for the Binary CEO Problem under Logarithmic Loss

Mahdi Nangir, Reza Asvadi, Jun Chen +2

The L-link binary Chief Executive Officer (CEO) problem under logarithmic loss is investigated in this paper. A quantization splitting technique is applied to convert the problem…

cs.IT2018

Successive Wyner-Ziv Coding for the Binary CEO Problem under Log-Loss

Mahdi Nangir, Reza Asvadi, Mahmoud Ahmadian-Attari +1

An l-link binary CEO problem is considered in this paper. We present a practical encoding and decoding scheme for this problem employing the graph-based codes. A successive codin…

cs.CV2018

Efficient Parallel Connected Components Labeling with a Coarse-to-fine Strategy

Jun Chen, Keisuke Nonaka, Ryosuke Watanabe +3

This paper proposes a new parallel approach to solve connected components on a 2D binary image implemented with CUDA. We employ the following strategies to accelerate neighborhood…

cs.IT2018

Binary CEO Problem under Log-Loss with BSC Test-Channel Model

Mahdi Nangir, Reza Asvadi, Mahmoud Ahmadian-Attari +1

In this paper, we propose an efficient coding scheme for the two-link binary Chief Executive Officer (CEO) problem under logarithmic loss criterion. The exact rate-distortion bound…

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