A Trillion Coral Reef Colors: Deeply Annotated Underwater Hyperspectral Images for Automated Classification and Habitat Mapping

A Trillion Coral Reef Colors: Deeply Annotated Underwater Hyperspectral Images for Automated Classification and Habitat Mapping

This paper describes a large dataset of underwater hyperspectral imagery that can be used by researchers in the domains of computer vision, machine learning, remote sensing, and coral reef ecology. We present the details of underwater data acquisition, processing and curation to create this large da...

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Bibliographic Details
Main Authors: Ahmad Rafiuddin Rashid, Arjun Chennu
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Data
Subjects:
hyperspectral imaging
proximal sensing
machine learning
hierarchical learning
coral reef
biodiversity
classification
habitat mapping
image segmentation
Online Access:https://www.mdpi.com/2306-5729/5/1/19

Internet

https://www.mdpi.com/2306-5729/5/1/19

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