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The amphibian lifecycle is more complicated compared to other animals, since they undergo metamorphosis.
The existing methods of tracking amphibians is not efficient, is costly and can adversely affect amphibian’s well-being and health conditions.
An app was built using computer vision and machine learning technology to accurately identify amphibians in the wild by unique pattern recognition matched against large number of species in its database.
Our AI engineers did a fantastic job to design the algorithm logic, but we also had to create a smart workflow logic as well. This endeavor was accomplished by our UI/UX engineers and statistical program analyst to build a user-friendly interphase for smooth delivery during their research.
They are able to capture photos of the subject amphibian, identify it, add description and store it under the right classification in the database.
Thanks to the great work of our team of engineers designing this computer vision algorithm, scientists can seamlessly view the numeric values of captured images of each subject amphibian in the database for further population analysis.
*All case studies are for illustration purposes only. Due to NDA agreements between the client and the development team, project details cannot be disclosed.