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Yang Wang

4 papers hereh-index 9542 citations18 works total

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

author position
  • middle author3

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • eess.IV1
same name
  • Yang Wang — 91 papers, h 102
  • Yang Wang — 34 papers, h 24
  • Yang Wang — 20 papers, h 14
  • Yang Wang — 19 papers, h 13
  • Yang Wang — 15 papers, h 3
  • Yang Wang — 14 papers, h 6

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
20162020
most citedMARTA GANs: Unsupervised Representation Learning for Remote Sensing Image Classification

242 citations · 389 across the 4 of their papers we have counts for

collaborators

4 papers

eess.IV2020★ 54 cited

High Quality Remote Sensing Image Super-Resolution Using Deep Memory Connected Network

Wenjia Xu, Guangluan Xu, Yang Wang +3

Single image super-resolution is an effective way to enhance the spatial resolution of remote sensing image, which is crucial for many applications such as target detection and ima…

cs.CV2020★ 18 cited

Where is the Model Looking At?--Concentrate and Explain the Network Attention

Wenjia Xu, Jiuniu Wang, Yang Wang +3

Image classification models have achieved satisfactory performance on many datasets, sometimes even better than human. However, The model attention is unclear since the lack of int…

cs.CV2019★ 75 cited

A Remote Sensing Image Dataset for Cloud Removal

Daoyu Lin, Guangluan Xu, Xiaoke Wang +3

Cloud-based overlays are often present in optical remote sensing images, thus limiting the application of acquired data. Removing clouds is an indispensable pre-processing step in…

cs.CV2016★ 242 cited

MARTA GANs: Unsupervised Representation Learning for Remote Sensing Image Classification

Daoyu Lin, Kun Fu, Yang Wang +2

With the development of deep learning, supervised learning has frequently been adopted to classify remotely sensed images using convolutional networks (CNNs). However, due to the l…

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