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researcher

Vishal M. Patel

4 papers hereh-index 7223 citations17 works total

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

author position
  • middle author3
  • last author1

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

fields
  • eess.SP2
  • cs.CV1
  • eess.SY1
same name
  • Vishal M. Patel — 163 papers, h 81
  • Vishal M. Patel — 9 papers, h 4
  • Vishal M. Patel — 9 papers, h 5
  • Vishal M. Patel — 9 papers, h 6
  • Vishal M. Patel — 8 papers, h 5
  • Vishal M. Patel — 8 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
20162022
most citedAn Efficient High-Dimensional Sparse Fourier Transform

2 citations · 2 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2022

Transformer-based SAR Image Despeckling

Malsha V. Perera, Wele Gedara Chaminda Bandara, Jeya Maria Jose Valanarasu +1

Synthetic Aperture Radar (SAR) images are usually degraded by a multiplicative noise known as speckle which makes processing and interpretation of SAR images difficult. In this pap…

eess.SP2017

Robust Sparse Fourier Transform Based on The Fourier Projection-Slice Theorem

Shaogang Wang, Vishal M. Patel, Athina Petropulu

The state-of-the-art automotive radars employ multidimensional discrete Fourier transforms (DFT) in order to estimate various target parameters. The DFT is implemented using the fa…

eess.SP2017

FPS-SFT: A Multi-dimensional Sparse Fourier Transform Based on the Fourier Projection-slice Theorem

Shaogang Wang, Vishal M. Patel, Athina Petropulu

We propose a multi-dimensional (M-D) sparse Fourier transform inspired by the idea of the Fourier projection-slice theorem, called FPS-SFT. FPS-SFT extracts samples along lines (1-…

eess.SY2016★ 2 cited

An Efficient High-Dimensional Sparse Fourier Transform

Shaogang Wang, Vishal M. Patel, Athina Petropulu

We propose RSFT, which is an extension of the one dimensional Sparse Fourier Transform algorithm to higher dimensions in a way that it can be applied to real, noisy data. The RSFT…

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