Our Work

Edammo helps our clients at a Recycling Operations Center to enhance their sorting process.

The Challenge

  • Client automates recycling center operations by using an overhead camera to find recyclable items on a conveyor belt
  • The images were cluttered from the camera resulting in only a 30% detectable rate using Google’s Auto ML framework based on Deep Learning and limited data

The Solution

Edammo developed an object detection front end application that leverages the Edammo engine and detects four types of recyclable object categories making detection decisions in real time

Results

Edammo 65% correct object detection, vs 30% from the Google baseline.