Pattern Recognition Application

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COMPUTER VISION CASE STUDY

Pattern Recognition Application

Client

A US based client asked us to build an app that can identify progressive changes within the population of amphibian (like frogs and newts) life cycle.

The amphibian lifecycle is more complicated compared to other animals, since they undergo metamorphosis.

PORBLEM
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.

The Challenge

Required to create a machine learning algorithm to accurately identify amphibians directly from their captured images/photos taken by user scientists using their smartphone camera.

Solution

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.

Results

The finished app is used as a tool by nature scientists to complement their work of 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.