Using Computer Vision to Identify the Sex of an Endangered Fish Species
|Affiliation||Biological and Agricultural Engineering, UC Davis|
|Project title||Using Computer Vision to Identify the Sex of an Endangered Fish Species|
|Background||Delta smelt is a federal and state listed endangered fish species in California Bay-Delta area. Their population number is very low so a captive population has been developed and maintained at the UC Davis Fish Conservation and Culture Lab (FCCL). The FCCL is functioning as a conservation hatchery since 1996 for research proposes and providing fish to researchers. One tricky thing for the fish is their sex can not be visually identified until the females have eggs ripe. This project is aiming for using machine learning and computer vision to develop a way to identify the sex of fish for future management purposes.|
|Description||Students working on this project will be training the computer with photos available at the FCCL and determine if there is a way the sex could be identified. The trained computer will be verified with blind testing, and the actual implementation (i.e. what the outcome could suggest researchers to identify the sex without running computers in the future) is expected.|
|Deliverable||• A trained system that could identify fish sex.
• Compare fish sex identification at different life stages.
• Recommendations to researchers regarding sex identification by actual morphometric measurements.
|Skill set desirable||N/A|
|Client time availability||30-60 min every two weeks|
|IP requirement||Open source project|