Deep Learning for Fruit Segmentation


Deep Learning for Fruit Segmentation

This project was part of a larger undertaking by the Precision Agriculture team at the Kumar Lab (GRASP, University of Pennsylvania)

Details regarding the project can be found in our paper title "Counting Apples and Oranges with Deep Learning: A Data Driven Approach" currently accepted into RAL 2017 and ICRA 2017.

The video shown below was our next endeavour into training our network on Mango data. Here just 21 2400x1600 mango images were trained for 10,000 iterations. The network was designed in Caffe using Python.

Performance on a few other datasets: