A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Filters
2020 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 13
2020
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Preserved Fulltext
., +, JSTARS 2020 5264-5271 Impact of Satellite Sounding Data on Virtual Visible Imagery Generation Using Conditional Generative Adversarial Network. ...
., +, JSTARS 2020 3701-3710 Impact of Satellite Sounding Data on Virtual Visible Imagery Generation Using Conditional Generative Adversarial Network. ...
doi:10.1109/jstars.2021.3050695
fatcat:ycd5qt66xrgqfewcr6ygsqcl2y
2021 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 14
2021
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Qi, Y., +, JSTARS 2021 6792-6806 Semisupervised Remote Sensing Image Fusion Using Multiscale Conditional Generative Adversarial Network With Siamese Structure. ...
., +, JSTARS 2021 2995-3005 Semisupervised Remote Sensing Image Fusion Using Multiscale Condi-tional Generative Adversarial Network With Siamese Structure. ...
., Hyperspectral Image Superresolution via Deep Structure and Texture Interfusion; JSTARS 2021 8665-8678 Hu, J., see Feng, D., JSTARS 2021 12212-12223 Hu, J., Shen, X., Yu, H., Shang, X., Guo, Q., ...
doi:10.1109/jstars.2022.3143012
fatcat:dnetkulbyvdyne7zxlblmek2qy
Table of Contents
2020
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Orban 4085 Change Detection in Unlabeled Optical Remote Sensing Data Using Siamese CNN .
and Z. ...
Wu Structure Aware Generative Adversarial Networks for Hyperspectral Image Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
Nian 4352 Hyperspectral Image Super Resolution Based on Multiscale Feature Fusion and Aggregation Network With 3-D Convolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
doi:10.1109/jstars.2020.3046663
fatcat:zqzyhnzacjfdjeejvzokfy4qze
Change Detection in Unlabeled Optical Remote Sensing Data using Siamese CNN
2020
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
We detect the changes by processing a pair of optical remote sensing images. ...
The proposed method adopts a patch-based approach, whereby we use a Siamese convolutional neural network (S-CNN), trained with augmented data, to compare successive pairs of patches obtained from the input ...
ACKNOWLEDGMENT The authors would like to thank the Archives of Quebec for providing historical aerial images of the city of Montreal. ...
doi:10.1109/jstars.2020.3009116
fatcat:q6libcvf4rdrtgz6osnj3lhcmu
A Review of Deep Learning in Multiscale Agricultural Sensing
2022
Remote Sensing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
To provide an update on these studies, we conducted a comprehensive investigation with a special emphasis on deep learning in multiscale agricultural remote and proximal sensing. ...
In precision agriculture (PA), non-destructive and non-invasive remote and proximal sensing methods have been widely used to observe crops in visible and invisible spectra. ...
Inception V3 network, a Siamese network with two subnets and contrastive loss, and a Siamese network with three subnets and triplet loss) with transfer learning were used [31] . ...
doi:10.3390/rs14030559
fatcat:fcgpljr2tfhpjd3nvmi3kgp3bq
Deep Learning for Hyperspectral Image Classification: An Overview
2019
IEEE Transactions on Geoscience and Remote Sensing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2019 pre-print arXiv:1910.12861v1 fatcat:wg6un4v2w5gk3ovyfm3qxajpli
Hyperspectral image (HSI) classification has become a hot topic in the field of remote sensing. ...
In addition, considering the fact that available training samples in the remote sensing field are usually very limited and training deep networks require a large number of samples, we include some strategies ...
In more detail, the well pretrained FCN-8 [72] was first used to explore deep multiscale spatial structural information. ...
doi:10.1109/tgrs.2019.2907932
fatcat:fepkjl3srnaqhakq4vlqvehfeu
2021 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 32
2021
IEEE Transactions on Neural Networks and Learning Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
., +, TNNLS March 2021 1124-1135 Image sequences Antidecay LSTM for Siamese Tracking With Adversarial Learning. ...
., +, TNNLS Feb. 2021 748-762 Condition monitoring A Neural Network-Based Joint Prognostic Model for Data Fusion and Remaining Useful Life Prediction. ...
Image coding Deep Multiscale Detail Networks for Multiband Spectral Image Sharpening. ...
doi:10.1109/tnnls.2021.3134132
fatcat:2e7comcq2fhrziselptjubwjme
Deep Induction Network for Small Samples Classification of Hyperspectral Images
2020
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
To address the problem, a deep model based on the induction network is designed in this article to improve the classification performance of HSI under the condition of small samples. ...
Specifically, the typical meta-training strategy is adopted, enabling the model to acquire stronger generalization ability, so as to accurately distinguish the new classes with only a few labeled samples ...
Yokoya for providing the HSI used in this article. The authors would also like to thank all the researchers for kindly providing the codes associated with the experiments. ...
doi:10.1109/jstars.2020.3002787
fatcat:vrh555bat5dxjnaa3c6e5a3yzy
2021 Index IEEE Transactions on Instrumentation and Measurement Vol. 70
2021
IEEE Transactions on Instrumentation and Measurement
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Article numbers are based on specified topic areas and corresponding codes associated with the publication. ...
., +, TIM 2021 5006011 Multiscale Convolutional Generative Adversarial Network for Anchorage Grout Defect Detection. ...
Sample Augmentation for Intelligent Milling Tool Wear Condition Monitoring Using Numerical Simulation and Generative Adversarial Network. ...
doi:10.1109/tim.2022.3156705
fatcat:dmqderzenrcopoyipv3v4vh4ry
A Comprehensive Survey of Machine Learning Applied to Radar Signal Processing
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
This work is amply introduced by providing general elements of ML-based RSP and by stating the motivations behind them. ...
The main applications of ML-based RSP are then analysed and structured based on the application field. ...
RFI radio frequency identification RMA range migration algorithm RNNs recurrent neural networks RS remote sensing RESISC remote sensing image scene classification RBF radial basis function REC radar emitter ...
arXiv:2009.13702v1
fatcat:m6am73324zdwba736sn3vmph3i
Hyperspectral Anomaly Detection Using Deep Learning: A Review
2022
Remote Sensing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY ...
Introduction 1.Hyperspectral Image and Applications In the field of remote sensing, hyperspectral image (HSI) is a ground image collected by advanced sensor technology and imaging system mounted on satellites ...
Conclusions HSI anomaly detection has received extensive attention in the field of remote sensing image processing. ...
doi:10.3390/rs14091973
dblp:journals/remotesensing/HuXFDZJWHLZCWC22
fatcat:vwb3azo7cjgopaj7lrbwp6wzki
2020 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 31
2020
IEEE Transactions on Neural Networks and Learning Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Yang, K., +, TNNLS April 2020 1387-1400 Image-Based Model Parameter Optimization Using Model-Assisted Generative Adversarial Networks. ...
., +, TNNLS Nov. 2020 5005-5013 Skip-Connected Covariance Network for Remote Sensing Scene Classification. ...
., +, TNNLS Oct. 2020 3777-3787 On the Working Principle of the Hopfield Neural Networks and its Equivalence to the GADIA in Optimization. Uykan, Z., ...
doi:10.1109/tnnls.2020.3045307
fatcat:34qoykdtarewhdscxqj5jvovqy
2021 Index IEEE Journal of Biomedical and Health Informatics Vol. 25
2021
IEEE journal of biomedical and health informatics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
., +, JBHI July 2021 2376-2387 COVID-19 CT Image Synthesis With a Conditional Generative Adversarial Network. ...
., +, JBHI July 2021 2376-2387 COVID-19 CT Image Synthesis With a Conditional Generative Adversarial Network. ...
doi:10.1109/jbhi.2022.3140980
fatcat:ufig7b54gfftnj3mocspoqbzq4
2021 Index IEEE Transactions on Industrial Informatics Vol. 17
2021
IEEE Transactions on Industrial Informatics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
., +, TII Aug. 2021 5369-5379 Dual-Domain-Based Adversarial Defense With Conditional VAE and Bayesian Network. ...
., +, TII April 2021 2400-2410 Dual-Domain-Based Adversarial Defense With Conditional VAE and Bayes-ian Network. ...
doi:10.1109/tii.2021.3138206
fatcat:ulsazxgmpfdmlivigjqgyl7zre
Artificial Intelligence in the Creative Industries: A Review
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
A brief background of AI, and specifically Machine Learning (ML) algorithms, is provided including Convolutional Neural Network (CNNs), Generative Adversarial Networks (GANs), Recurrent Neural Networks ...
We further differentiate between the use of AI as a creative tool and its potential as a creator in its own right. ...
Image Enhancement Conditional Generative Adversarial Networks (IE-CGANs) designed to process both visible and infrared images have been proposed by Kuang et al. (2019) . ...
arXiv:2007.12391v5
fatcat:mn2xqeylyrbabbu5zwln3admtm
« Previous
Showing results 1 — 15 out of 18 results