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researcher

M. Onishi

4 papers here

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

author position
  • middle author4

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

fields
  • cs.CV2
  • cs.DC1
  • cs.SD1
same name
  • M. Onishi — 3 papers
  • M. Onishi — 2 papers, h 7
  • M. Onishi — 1 paper, h 13
  • M. Onishi — 1 paper, h 5

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
20202022
most citedBlock-wise Scrambled Image Recognition Using Adaptation Network

31 citations · 33 across the 4 of their papers we have counts for

collaborators

4 papers

cs.DC2022

Fast convolution kernels on pascal GPU with high memory efficiency

Qiong Chang, Masaki Onishi, Tsutomu Maruyama

The convolution computation is widely used in many fields, especially in CNNs. Because of the rapid growth of the training data in CNNs, GPUs have been used for the acceleration, a…

cs.CV2021

Heterogeneous Grid Convolution for Adaptive, Efficient, and Controllable Computation

Ryuhei Hamaguchi, Yasutaka Furukawa, Masaki Onishi +1

This paper proposes a novel heterogeneous grid convolution that builds a graph-based image representation by exploiting heterogeneity in the image content, enabling adaptive, effic…

cs.SD2020★ 2 cited

Self-supervised Neural Audio-Visual Sound Source Localization via Probabilistic Spatial Modeling

Yoshiki Masuyama, Yoshiaki Bando, Kohei Yatabe +3

Detecting sound source objects within visual observation is important for autonomous robots to comprehend surrounding environments. Since sounding objects have a large variety with…

cs.CV2020★ 31 cited

Block-wise Scrambled Image Recognition Using Adaptation Network

Koki Madono, Masayuki Tanaka, Masaki Onishi +1

In this study, a perceptually hidden object-recognition method is investigated to generate secure images recognizable by humans but not machines. Hence, both the perceptual informa…

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