Deep metric learning (DML) based methods have been found very effective ...
Due to the publicly available thematic maps and crowd-sourced data, remo...
The development of federated learning (FL) methods, which aim to learn f...
The development of deep learning based image representation learning (IR...
Due to the availability of multi-modal remote sensing (RS) image archive...
This paper introduces a novel deep metric learning-based semi-supervised...
Remote sensing (RS) images are usually stored in compressed format to re...
This paper presents a novel graph-theoretic deep representation learning...
This paper presents the multi-modal BigEarthNet (BigEarthNet-MM) benchma...
This paper analyzes and compares different deep learning loss functions ...
To reduce the storage requirements, remote sensing (RS) images are usual...
Deep neural networks (DNNs) have been recently found popular for image
c...
This chapter presents recent advances in content based image search and
...
Success of deep neural networks in the framework of remote sensing (RS) ...
This paper presents a Generative Adversarial Network based super-resolut...
This paper presents a novel framework that jointly exploits Convolutiona...
This paper presents a new large-scale multi-label Sentinel-2 benchmark
a...
Fine-grained object recognition concerns the identification of the type ...
Fine-grained object recognition that aims to identify the type of an obj...