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Qingfeng Guan

3 papers here

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

author position
  • middle author3

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

fields
  • cs.CY2
  • cs.CV1

identity via Semantic Scholar / OpenAlex

most citedA Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image Classification

191 citations · 240 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CV2021★ 191 cited

A Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image Classification

Qiqi Zhu, Weihuan Deng, Zhuo Zheng +5

Deep learning techniques have been widely applied to hyperspectral image (HSI) classification and have achieved great success. However, the deep neural network model has a large pa…

cs.CY2021★ 8 cited

UrbanVCA: a vector-based cellular automata framework to simulate the urban land-use change at the land-parcel level

Yao Yao, Linlong Li, Zhaotang Liang +9

Vector-based cellular automata (CA) based on real land-parcel has become an important trend in current urban development simulation studies. Compared with raster-based and parcel-b…

cs.CY2020★ 41 cited

Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: A case study in Wuhan, China

Xun Liang, Qingfeng Guan, Keith C. Clarke +3

Cellular Automata (CA) are widely used to model the dynamics within complex land use and land cover (LULC) systems. Past CA model research has focused on improving the technical mo…

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