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Bayesian Convolutional Neural Networks for Limited Data Hyperspectral
  Remote Sensing Image Classification

Bayesian Convolutional Neural Networks for Limited Data Hyperspectral Remote Sensing Image Classification

19 May 2022
M. Joshaghani
Amirabbas Davari
F. Hatamian
Andreas K. Maier
Christian Riess
    UQCV
    BDL
ArXivPDFHTML

Papers citing "Bayesian Convolutional Neural Networks for Limited Data Hyperspectral Remote Sensing Image Classification"

11 / 11 papers shown
Title
Generative Adversarial Networks
Generative Adversarial Networks
Gilad Cohen
Raja Giryes
GAN
280
30,103
0
01 Mar 2022
Synthetic Glacier SAR Image Generation from Arbitrary Masks Using
  Pix2Pix Algorithm
Synthetic Glacier SAR Image Generation from Arbitrary Masks Using Pix2Pix Algorithm
Rosanna Dietrich-Sussner
Amirabbas Davari
T. Seehaus
M. Braun
Vincent Christlein
Andreas Maier
Christian Riess
GAN
33
9
0
08 Jan 2021
Deep Learning for Classification of Hyperspectral Data: A Comparative
  Review
Deep Learning for Classification of Hyperspectral Data: A Comparative Review
Nicolas Audebert
Bertrand Le Saux
Sébastien Lefèvre
85
478
0
24 Apr 2019
A Comprehensive guide to Bayesian Convolutional Neural Network with
  Variational Inference
A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference
Kumar Shridhar
F. Laumann
Marcus Liwicki
BDL
UQCV
81
174
0
08 Jan 2019
HSI-CNN: A Novel Convolution Neural Network for Hyperspectral Image
HSI-CNN: A Novel Convolution Neural Network for Hyperspectral Image
Yanan Luo
Jie Zou
Chengfei Yao
Tao Li
Gang Bai
33
133
0
28 Feb 2018
GMM-Based Synthetic Samples for Classification of Hyperspectral Images
  With Limited Training Data
GMM-Based Synthetic Samples for Classification of Hyperspectral Images With Limited Training Data
Amirabbas Davari
E. Aptoula
Berrin Yanikoglu
Andreas Maier
Christian Riess
33
34
0
13 Dec 2017
Spectral-spatial classification of hyperspectral images: three tricks
  and a new supervised learning setting
Spectral-spatial classification of hyperspectral images: three tricks and a new supervised learning setting
Jacopo Acquarelli
Elena Marchiori
Lutgarde M. C. Buydens
Thanh Tran
Twan van Laarhoven
35
42
0
15 Nov 2017
Learning from Simulated and Unsupervised Images through Adversarial
  Training
Learning from Simulated and Unsupervised Images through Adversarial Training
A. Shrivastava
Tomas Pfister
Oncel Tuzel
J. Susskind
Wenda Wang
Russ Webb
GAN
103
1,801
0
22 Dec 2016
Variational Dropout and the Local Reparameterization Trick
Variational Dropout and the Local Reparameterization Trick
Diederik P. Kingma
Tim Salimans
Max Welling
BDL
226
1,514
0
08 Jun 2015
Bayesian Convolutional Neural Networks with Bernoulli Approximate
  Variational Inference
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
Y. Gal
Zoubin Ghahramani
UQCV
BDL
258
751
0
06 Jun 2015
Weight Uncertainty in Neural Networks
Weight Uncertainty in Neural Networks
Charles Blundell
Julien Cornebise
Koray Kavukcuoglu
Daan Wierstra
UQCV
BDL
187
1,887
0
20 May 2015
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