AFID
Automated Fish Identification
The Digital Assistant for EventMeasure
Project Mission
Reduce the cost and manual labour required to monitor our sensitive maritime ecosystem through data science
Machine Learning Based Digital Assistant
The AFID Digital assistant is being developed for EventMeasure
Watch AFID in action on YouTube
AFID uses Machine Learning to suggest species right inside EventMeasure
AFID autonomously detects the head and tail of fish and uses EventMeasure's calibration methods to accurately measure the length of the fish.
Automated Fish Length Measurements
Automated Species Classification
Relative Species Abundance
Finding MaxN frames, running MaxN and average MaxN
Open Source
Questions?
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AFID is currently in the proof of concept stage of the BRII - AIMS challenge. If you have data to contribute to public datasets, time to contribute to machine learning algorithms, or would like to be part of our stakeholder group, please contact Dan Marrable to get more information about the project
Project Partners :
With Support From:
