Open AccessA novel approach for Hyper Spectral Images using Transfer Learning
Author(s) -
Rohit Bharti,
Dipen Saini,
Rahul Malik
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1022/1/012120
Subject(s) - transfer of learning , computer science , constraint (computer aided design) , computation , artificial intelligence , transfer (computing) , deep learning , cover (algebra) , machine learning , pattern recognition (psychology) , algorithm , mathematics , mechanical engineering , geometry , parallel computing , engineering
The spectral analysis and spatial analysis of high dimensional images are very important and in this paper we tried to cover some aspects that how this problem can be handled and proposed a way through which we can overcome the problem of the time constraint and using some deep learning novel approach like transfer learning for getting the best results while performing the actual computations and the results which we obtained. The dataset used is EuroSAT in which by using a VGG network, the accuracy is achieved 95 per cent and the validation accuracy achieved is 92 per cent. Also, the Kappa score which we got for this observation is 0.95. The tool used for the implementation purpose is TensorFlow with GPU which is also discussed in the paper.