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researcher

Masayuki Tanaka

25 papers hereh-index 293.6k citations177 works total

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

author position
  • sole author1
  • first author2
  • middle author16
  • last author6

Across the 25 of 25 papers where every author was matched, so the position is known.

fields
  • cs.CV19
  • eess.IV3
  • cs.LG2
  • astro-ph.GA1
Homepage
same name
  • Masayuki Tanaka — 168 papers, h 56
  • Masayuki Tanaka — 22 papers, h 29
  • Masayuki Tanaka — 19 papers, h 7
  • Masayuki Tanaka — 8 papers, h 3
  • Masayuki Tanaka — 3 papers, h 5
  • Masayuki Tanaka — 3 papers, h 2

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
20172026
most citedUnsupervised Learning of Image Segmentation Based on Differentiable Feature Clustering

253 citations · 310 across the 24 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

cs.CV2018★ 3 cited

Estimation and Restoration of Compositional Degradation Using Convolutional Neural Networks

Kazutaka Uchida, Masayuki Tanaka, Masatoshi Okutomi

Image restoration from a single image degradation type, such as blurring, hazing, random noise, and compression has been investigated for decades. However, image degradations in pr…

cs.CV2018★ 1 cited

Gradient-Based Low-Light Image Enhancement

Masayuki Tanaka, Takashi Shibata, Masatoshi Okutomi

A low-light image enhancement is a highly demanded image processing technique, especially for consumer digital cameras and cameras on mobile phones. In this paper, a gradient-based…

cs.CV2018★ 3 cited

Non-blind Image Restoration Based on Convolutional Neural Network

Kazutaka Uchida, Masayuki Tanaka, Masatoshi Okutomi

Blind image restoration processors based on convolutional neural network (CNN) are intensively researched because of their high performance. However, they are too sensitive to the…

cs.CV2018★ 4 cited

Learnable Image Encryption

Masayuki Tanaka

The network-based machine learning algorithm is very powerful tools. However, it requires huge training dataset. Researchers often meet privacy issues when they collect image datas…

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