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researcher

R. Chan

15 papers hereh-index 5010.4k citations213 works total

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

author position
  • first author3
  • middle author10
  • last author1

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

fields
  • cs.CV4
  • eess.IV4
  • cs.LG2
  • math.OC2
  • astro-ph.IM1
  • eess.SP1
same name
  • R. Chan — 16 papers, h 7
  • R. Chan — 8 papers, h 22
  • R. Chan — 3 papers
  • R. Chan — 3 papers, h 22
  • R. Chan — 3 papers, h 2
  • R. Chan — 2 papers, h 1

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 citedDeep Tensor CCA for Multi-view Learning

4 citations · 10 across the 9 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2022

Unsupervised Spatial-spectral Hyperspectral Image Reconstruction and Clustering with Diffusion Geometry

Kangning Cui, Ruoning Li, Sam L. Polk +3

Hyperspectral images, which store a hundred or more spectral bands of reflectance, have become an important data source in natural and social sciences. Hyperspectral images are oft…

cs.CV2022

A 3-stage Spectral-spatial Method for Hyperspectral Image Classification

Raymond H. Chan, Ruoning Li

Hyperspectral images often have hundreds of spectral bands of different wavelengths captured by aircraft or satellites that record land coverage. Identifying detailed classes of pi…

cs.CV2022★ 2 cited

Classification of Hyperspectral Images Using SVM with Shape-adaptive Reconstruction and Smoothed Total Variation

Ruoning Li, Kangning Cui, Raymond H. Chan +1

In this work, a novel algorithm called SVM with Shape-adaptive Reconstruction and Smoothed Total Variation (SaR-SVM-STV) is introduced to classify hyperspectral images, which makes…

cs.CV2019

Dynamic Spectral Residual Superpixels

Jianchao Zhang, Angelica I. Aviles-Rivero, Daniel Heydecker +3

We consider the problem of segmenting an image into superpixels in the context of k-means clustering, in which we wish to decompose an image into local, homogeneous regions corre…

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