A fast and compact 3-D CNN for hyperspectral image classification
Hyperspectral images (HSIs) are used in a large number of real-world applications. HSI
classification (HSIC) is a challenging task due to high interclass similarity, high intraclass …
classification (HSIC) is a challenging task due to high interclass similarity, high intraclass …
Partial domain adaptation for scene classification from remote sensing imagery
Although domain adaptation approaches have been proposed to tackle cross-regional,
multitemporal, and multisensor remote sensing applications since they do not require any …
multitemporal, and multisensor remote sensing applications since they do not require any …
A Two-Stage Adaptation Network (TSAN) for Remote Sensing Scene Classification in Single-Source-Mixed-Multiple-Target Domain Adaptation (S²M²T DA) …
Over the past decade, domain adaptation (DA) algorithms have been proposed to address
domain gap problems as they do not need any interpretation in the target domain. However …
domain gap problems as they do not need any interpretation in the target domain. However …
Open-set domain adaptation for scene classification using multi-adversarial learning
Abstract Domain adaptation methods are able to transfer knowledge across different
domains, tackling multi-sensor, multi-temporal or cross-regional remote sensing scenarios …
domains, tackling multi-sensor, multi-temporal or cross-regional remote sensing scenarios …
Multispectral and SAR image fusion based on Laplacian pyramid and sparse representation
Complementary information from multi-sensors can be combined to improve the availability
and reliability of stand-alone data. Typically, multispectral (MS) images contain plentiful …
and reliability of stand-alone data. Typically, multispectral (MS) images contain plentiful …
Locality Robust Domain Adaptation for cross-scene hyperspectral image classification
Abstract Domain adaptation (DA) has become a widely used technique for cross-scene
hyperspectral image (HSI) classification. Most DA methods aim to learn a domain invariant …
hyperspectral image (HSI) classification. Most DA methods aim to learn a domain invariant …
Domain adaptive remote sensing scene recognition via semantic relationship knowledge transfer
Scene recognition has attracted rising attentions of many researchers in the remote sensing
fields, owing to the rapidly advancing of remote sensing devices in recent years. However …
fields, owing to the rapidly advancing of remote sensing devices in recent years. However …
Collaboration between multiple experts for knowledge adaptation on multiple remote sensing sources
Due to the unique characteristics of remote sensing (RS) data, it is challenging to collect
richer labeled samples for training the deep learning model compared with the natural …
richer labeled samples for training the deep learning model compared with the natural …
Attention-guided multispectral and panchromatic image classification
C Shi, Y Dang, L Fang, Z Lv, H Shen - Remote Sensing, 2021 - mdpi.com
Multi-sensor image can provide supplementary information, usually leading to better
performance in classification tasks. However, the general deep neural network-based multi …
performance in classification tasks. However, the general deep neural network-based multi …
Him-Net: A New Neural Network Approach for SAR and Optical Image Template Matching1
SAR and optical images provide highly complementary information about observed scenes.
The integrated use of these two data is desired in many data fusion tasks. However …
The integrated use of these two data is desired in many data fusion tasks. However …