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Hyunjin Kim

4 papers hereh-index 7284 citations15 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.CV2
  • cs.LG2
same name
  • Hyunjin Kim — 9 papers, h 15
  • Hyunjin Kim — 8 papers, h 4
  • Hyunjin Kim — 6 papers, h 1
  • Hyunjin Kim — 3 papers, h 2
  • Hyunjin Kim — 1 paper, h 6
  • Hyunjin Kim — 1 paper, h 0

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 citedThe Effects of Approximate Multiplication on Convolutional Neural Networks

73 citations · 135 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023★ 4 cited

SyncDiffusion: Coherent Montage via Synchronized Joint Diffusions

Yuseung Lee, Kunho Kim, Hyunjin Kim +1

The remarkable capabilities of pretrained image diffusion models have been utilized not only for generating fixed-size images but also for creating panoramas. However, naive stitch…

cs.CV2022★ 1 cited

CTMQ: Cyclic Training of Convolutional Neural Networks with Multiple Quantization Steps

HyunJin Kim, Jungwoo Shin, Alberto A. Del Barrio

This paper proposes a training method having multiple cyclic training for achieving enhanced performance in low-bit quantized convolutional neural networks (CNNs). Quantization is…

cs.LG2021★ 57 cited

PLAM: a Posit Logarithm-Approximate Multiplier

Raul Murillo, Alberto A. Del Barrio, Guillermo Botella +3

The Posit Number System was introduced in 2017 as a replacement for floating-point numbers. Since then, the community has explored its application in Neural Network related tasks a…

cs.LG2020★ 73 cited

The Effects of Approximate Multiplication on Convolutional Neural Networks

Min Soo Kim, Alberto A. Del Barrio, HyunJin Kim +1

This paper analyzes the effects of approximate multiplication when performing inferences on deep convolutional neural networks (CNNs). The approximate multiplication can reduce the…

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