activity
20172022
most citedDeep Learning for Hyperspectral Image Classification: An Overview

1.9k citations · 1.9k across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV202257 cited

Asymmetric Hash Code Learning for Remote Sensing Image Retrieval

Weiwei Song, Zhi Gao, Renwei Dian +3

Remote sensing image retrieval (RSIR), aiming at searching for a set of similar items to a given query image, is a very important task in remote sensing applications. Deep hashing…

cs.CV2020

Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)

Behnood Rasti, Danfeng Hong, Renlong Hang +4

Hyperspectral images provide detailed spectral information through hundreds of (narrow) spectral channels (also known as dimensionality or bands) with continuous spectral informati…

astro-ph.EP2019

Lunar impact craters identification and age estimation with Chang'E data by deep and transfer learning

Chen Yang, Haishi Zhao, Lorenzo Bruzzone +7

Impact craters, as "lunar fossils", are the most dominant lunar surface features and occupy most of the Moon's surface. Their formation and evolution record the history of the Sola…

eess.IV20191.9k cited

Deep Learning for Hyperspectral Image Classification: An Overview

Shutao Li, Weiwei Song, Leyuan Fang +3

Hyperspectral image (HSI) classification has become a hot topic in the field of remote sensing. In general, the complex characteristics of hyperspectral data make the accurate clas…

cs.CV2019

Deep Hashing Learning for Visual and Semantic Retrieval of Remote Sensing Images

Weiwei Song, Shutao Li, Jon Atli Benediktsson

Driven by the urgent demand for managing remote sensing big data, large-scale remote sensing image retrieval (RSIR) attracts increasing attention in the remote sensing field. In ge…

cs.LG201813 cited

Multisource and Multitemporal Data Fusion in Remote Sensing

Pedram Ghamisi, Behnood Rasti, Naoto Yokoya +9

The sharp and recent increase in the availability of data captured by different sensors combined with their considerably heterogeneous natures poses a serious challenge for the eff…