Machine learning for planetary science. (2021)

• Record Type: Book
• Further Information: Note: Edited by Joern Helbert, Mario D'Amore, Michael Aye, Hannah Kerner.
• Editors: Helbert, Joern; D'Amore, Mario; Aye, Michael; Kerner, Hannah
• Contents: Part I: Introduction to Machine Learning 1. Types of ML methods (supervised, unsupervised, semi-supervised; classification, regression) 2. Dealing with small labeled datasets (semi-supervised learning, active learning) 3. Selecting a methodology and evaluation metrics 4. Interpreting and explaining model behavior 5. Hyperparameter optimization and training neural networks Part II: Methods of machine learning 6. The new and unique challenges of planetary missions 7. Data acquisition (PDS nodes, etc.) and Data types, projections, processing, units, etc. Part III: Useful tools for machine learning projects in planetary science 8. The Python Spectral Analysis Tool (PySAT): A Powerful, Flexible, Preprocessing and Machine Learning Library and Interface 9. Getting data from the PDS, pre-processing, and labeling it Part IV: Case studies 10. Enhancing Spatial Resolution of Remotely Sensed Imagery Using Deep Learning and/or Data Restoration 11. Surface mapping via unsupervised learning and clustering of Mercury’s Visible–Near-Infrared reflectance spectra 12. Mapping Saturn using deep learning 13. Artificial Intelligence for Planetary Data Analytics - Computer Vision to Boost Detection and Analysis of Jupiter's White Ovals in Images Acquired by the Jiram Spectrometer
• Publisher Details: Amsterdam : Elsevier
• Publication Date: 2021
• Extent: 1 online resource, illustrations
• Subjects: 523.20285631; Planetary science -- Data processing; Machine learning
• Languages: English
• ISBNs: 9780128187227
• Related ISBNs: 9780128187210
• Notes: Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.