Hyperspectral Image Classification for Vegetation Detection Using Lightweight Cascaded Deep Convolutional Neural Network

Sandhya Shinde; Hemant Patidar

doi:10.1007/s12524-023-01754-5

ScienceGate Book Chapters

JOURNAL ARTICLE

Hyperspectral Image Classification for Vegetation Detection Using Lightweight Cascaded Deep Convolutional Neural Network

Sandhya Shinde Hemant Patidar

Year: 2023 Journal: Journal of the Indian Society of Remote Sensing Vol: 51 (11)Pages: 2159-2166 Publisher: Springer Science+Business Media

DOI: 10.1007/s12524-023-01754-5

Get Full-Text PDF Get Analytical Report

Keywords:

Hyperspectral imaging Convolutional neural network Artificial intelligence Pattern recognition (psychology) Computer science Field (mathematics) Principal component analysis Image (mathematics) Vegetation (pathology) Linear discriminant analysis Deep learning Artificial neural network Mathematics

Metrics

Cited By

0.65

FWCI (Field Weighted Citation Impact)

Refs

0.69

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Remote-Sensing Image Classification

Physical Sciences → Engineering → Media Technology

Remote Sensing and Land Use

Physical Sciences → Earth and Planetary Sciences → Atmospheric Science

Spectroscopy and Chemometric Analyses

Physical Sciences → Chemistry → Analytical Chemistry

Hyperspectral Image Classification for Vegetation Detection Using Lightweight Cascaded Deep Convolutional Neural Network

Metrics

Citation History

Topics

Related Documents

Classification of hyperspectral images by using a lightweight cascaded deep convolutional network

Hyperspectral Image Classification using Hybrid Deep Convolutional Neural Network

A Lightweight Convolutional Neural Network for Hyperspectral Image Classification

Hyperspectral image classification using two-channel deep convolutional neural network

Classification of hyperspectral images by utilising a lightweight cascaded deep convolutional network