International Journal of Electrical, Electronics and Data Communication (IJEEDC)
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Statistics report
Apr. 2024
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 133
Paper Published : 1712
No. of Authors : 4737
  Journal Paper


Paper Title :
Variational-Auto Encoder Siamese Network for Change Detection on Satellite Imagery

Author :Aritro Pal Choudhury, Soumyo Nath Tripathy, Tamesh Halder,Shaunak De, Rintu Kumar Gayen, Debashish Chakravarty

Article Citation :Aritro Pal Choudhury ,Soumyo Nath Tripathy ,Tamesh Halder ,Shaunak De ,Rintu Kumar Gayen ,Debashish Chakravarty , (2023 ) " Variational-Auto Encoder Siamese Network for Change Detection on Satellite Imagery " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 29-33, Volume-11,Issue-6

Abstract : Capturing changes in certain areas has assumed huge importance due to both man-made and natural phenomenon. Our novel research is aimed at urban classification using an unsupervised Variational Auto-encoder based Siamese network model for change detection on satellite imagery. It works well on Polarimetric Synthetic Aperture Radar (PolSAR) images of Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) as well as optical satellite images. The model encodes the images to get the latent feature vectors, on which the Siamese difference is performed and the resultant latent space is decoded to get the difference image. The metrics which help us determine how well our model predicts the mask are the recall score and the receiver operating characteristic curve. We have archived a recall score of 0.87 and the area under the receiver operating characteristic curve is 0.98 Keywords - Change Detection, Variational Auto Encoder, Siamese Network, Receiver Operating Characteristic Curve, Latent Features, unsupervised.

Type : Research paper

Published : Volume-11,Issue-6


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