One-Dimensional Convolutional Neural Network Land-Cover Classification of Multi-Seasonal Hyperspectral Imagery in the San Francisco Bay Area, California
Published 2017 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
One-Dimensional Convolutional Neural Network Land-Cover Classification of Multi-Seasonal Hyperspectral Imagery in the San Francisco Bay Area, California
Authors
Keywords
-
Journal
Remote Sensing
Volume 9, Issue 6, Pages 629
Publisher
MDPI AG
Online
2017-06-20
DOI
10.3390/rs9060629
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data
- (2017) Nataliia Kussul et al. IEEE Geoscience and Remote Sensing Letters
- Transferring Pre-Trained Deep CNNs for Remote Scene Classification with General Features Learned from Linear PCA Network
- (2017) Jie Wang et al. Remote Sensing
- Spectral–Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network
- (2017) Ying Li et al. Remote Sensing
- A Convolutional Neural Network Approach for Assisting Avalanche Search and Rescue Operations with UAV Imagery
- (2017) Mesay Bejiga et al. Remote Sensing
- Spectral–Spatial Feature Extraction for Hyperspectral Image Classification: A Dimension Reduction and Deep Learning Approach
- (2016) Wenzhi Zhao et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Mapping of land cover in northern California with simulated hyperspectral satellite imagery
- (2016) Matthew L. Clark et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Mapping methane concentrations from a controlled release experiment using the next generation airborne visible/infrared imaging spectrometer (AVIRIS-NG)
- (2016) A.K. Thorpe et al. REMOTE SENSING OF ENVIRONMENT
- A meta-analysis of remote sensing research on supervised pixel-based land-cover image classification processes: General guidelines for practitioners and future research
- (2016) Reza Khatami et al. REMOTE SENSING OF ENVIRONMENT
- Salient Band Selection for Hyperspectral Image Classification via Manifold Ranking
- (2016) Qi Wang et al. IEEE Transactions on Neural Networks and Learning Systems
- Deep Learning Based Oil Palm Tree Detection and Counting for High-Resolution Remote Sensing Images
- (2016) Weijia Li et al. Remote Sensing
- Classification and Segmentation of Satellite Orthoimagery Using Convolutional Neural Networks
- (2016) Martin Längkvist et al. Remote Sensing
- Hyperspectral Imagery Classification Using Sparse Representations of Convolutional Neural Network Features
- (2016) Heming Liang et al. Remote Sensing
- Hyperspectral Image Classification via Multitask Joint Sparse Representation and Stepwise MRF Optimization
- (2016) Yuan Yuan et al. IEEE Transactions on Cybernetics
- An introduction to the NASA Hyperspectral InfraRed Imager (HyspIRI) mission and preparatory activities
- (2015) Christine M. Lee et al. REMOTE SENSING OF ENVIRONMENT
- Atmospheric correction for global mapping spectroscopy: ATREM advances for the HyspIRI preparatory campaign
- (2015) David R. Thompson et al. REMOTE SENSING OF ENVIRONMENT
- Transferring Deep Convolutional Neural Networks for the Scene Classification of High-Resolution Remote Sensing Imagery
- (2015) Fan Hu et al. Remote Sensing
- Deep Convolutional Neural Networks for Hyperspectral Image Classification
- (2015) Wei Hu et al. Journal of Sensors
- Spectral-Spatial Classification of Hyperspectral Image Based on Kernel Extreme Learning Machine
- (2014) Chen Chen et al. Remote Sensing
- Convolutional Neural Networks for Speech Recognition
- (2014) Ossama Abdel-Hamid et al. IEEE-ACM Transactions on Audio Speech and Language Processing
- Endmember variability in Spectral Mixture Analysis: A review
- (2011) Ben Somers et al. REMOTE SENSING OF ENVIRONMENT
- Support vector machines in remote sensing: A review
- (2010) Giorgos Mountrakis et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Hierarchical Multiple Endmember Spectral Mixture Analysis (MESMA) of hyperspectral imagery for urban environments
- (2009) Jonas Franke et al. REMOTE SENSING OF ENVIRONMENT
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started