Explore
![Deep Learning and Transformers’ Methods Applied to Remotely Captured Data Deep Learning and Transformers’ Methods Applied to Remotely Captured Data](/static/images/generic_cover_larger.png)
Deep Learning and Transformers’ Methods Applied to Remotely Captured Data
0 Ungluers have
Faved this Work
Login to Fave
The areas of machine learning and deep learning have experienced impressive progress in recent years. This progress has mainly been driven by the availability of high processing performance at an affordable cost and a large quantity of data. Most state-of-the-art techniques today are based on deep neural networks or the more recently proposed transformers. This progress has sparked innovations in technologies, algorithms, and approaches and led to results that were unachievable until recently. Among the various research areas that have been significantly impacted by this progress is the processing of remotely captured data such as airborne and spaceborne passive and active imagery, underwater imagery, mobile mapping data, etc. This collection gathered cutting-edge contributions from researchers using deep learning and transformers for remote sensing and for processing remotely captured data.
This book is included in DOAB.
Why read this book? Have your say.
You must be logged in to comment.
Rights Information
Are you the author or publisher of this work? If so, you can claim it as yours by registering as an Unglue.it rights holder.Downloads
This work has been downloaded 0 times via unglue.it ebook links.
- 0 - pdf (CC BY-NC-ND) at Unglue.it.
Keywords
- deep learning
- image classification
- LiDAR data
- Point Cloud Transformer
- Remote sensing
- Satellite Imaging
- ship detection
- super-resolution
- terrain analysis
- transformer models
Links
DOI: 10.3390/books978-3-7258-0586-0Editions
![edition cover edition cover](/static/images/generic_cover_larger.png)