Time machine biology and the development of AI-based automatic identifications in Hong Kong: Paleobiology to better understand biodiversity of marine ecosystems

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Grant Data
Project Title
Time machine biology and the development of AI-based automatic identifications in Hong Kong: Paleobiology to better understand biodiversity of marine ecosystems
Principal Investigator
Professor Yasuhara, Moriaki   (Principal Investigator (PI))
Duration
60
Start Date
2023-01-01
Amount
5155380
Conference Title
Time machine biology and the development of AI-based automatic identifications in Hong Kong: Paleobiology to better understand biodiversity of marine ecosystems
Keywords
Ostracoda, micropaleontology, Paleoecology, Macroevolution, Marine biodiversity
Discipline
Others - Physical SciencesEnvironmental Studies and Science
HKU Project Code
RFS2223-7S02
Grant Type
RGC Research Fellow Scheme (RFS) 2022/23
Funding Year
2022
Status
On-going
Objectives
(1) to develop the automated imaging and identification system in HKU (2) to apply this system to a model system microfossil ostracod (3) to use the resulting microfossil automated identification system to historical ecology and paleoenvironmental reconstructions (4) to establish Time Machine Biology in Hong Kong (5) to understand Hong Kong ecosystem history quantitatively