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Development of deep learning based automatic approach for marine habitat monitoring from remote sensing and visual imagery

Project Outline

Remote sensing imagery contains crucial information that can be used for monitoring the Earth’s environmental and natural resources. This project aims to develop a state-of-the art deep learning based efficient approach for monitoring seagrass and other marine habitats from different remote sensing and visual data. The automatic analysis of the multimodal data proposed in this project will not only enhance cross discipline research collaboration but will also provide industry engagement opportunity especially with the Department of Biodiversity, Conservation and Attractions (DBCA) and The Western Australian Marine Science Institution (WAMSI) by
facilitating automation in many of their existing and emerging services.

Preferred Applicant Skillset

We are looking for a self-motivated PhD candidate with excellent computer programming,  organisation, problem-solving and project management skills. Candidates with strong quantitative skills including familiarity with SPSS and state of the art deep learning approaches are desired.

Internship Opportunity

There is opportunity of internship with the Department of Biodiversity, Conservation and Attractions (DBCA) and The Western Australian Marine Science Institution (WAMSI). The proposed supervisors have worked with them in different projects in the past.

Primary Contact
Dr Syed Mohamemd Shamsul Islam
+61 416 541 554
Syed.islam@ecu.edu.au

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