Understandably, with pressure from product teams to deliver value quickly for end-users, potential features are tossed aside in a backlog abyss.

You need the right in-house expertise to collect data, train a model, and iterate on the performance and accuracy. Many engineering teams cannot justify the time and resources. The middle one is a poodle dressed up as Toothless for Halloweenīut creating features powered by machine learning isn’t easy. In plain English, object detection identifies and locates specific items in an image or live video with a bounding box. With the rise of mobile frameworks like TensorFlow Lite and Core ML, more and more mobile apps leverage the power of machine learning to create features that leave us in awe. Whether it is detecting plant damage for farmers, tracking vehicles on the road, or monitoring your pets - the applications for object detection are endless. By Eric Hsiao A guide to Object Detection with Fritz: Build a pet monitoring app in Android with machine learning