Contact
How to shop
Delivery
Shopping guide
Deep Learning Classifiers for Hyperspectral Image Analysis
English
162 b
30-day return policy
Hyperspectral image classification is the most popular research area in the hyperspectral community and has attracted significant interest in remote sensing. HSI classification is a challenging task because of the large dimensionality of the data, inadequate datasets, huge data, and limited training samples. Several Deep Learning (DL) based architectures are being explored to resolve the aforementioned challenges and provide significant improvements in HSI data analysis. Limited studies have been presented in the literature in the direction of exploring deep learning architectures for joint spatial and spectral features to achieve high accuracy of pixel classification. This book presents different deep-learning approaches for efficient spatial-spectral features for the classification of pixels in HSI images.
About the book
English
Give this book today
It's easy
1 Add to cart and choose Deliver as present at the checkout 2 We'll send you a voucher 3 The book will arrive at the recipient's addressHi! I'm Libroamiko, your book advisor.
How can I help you?