Deep Learning

For quantitative analysis, cells in microscopic images need to be segmented from the image. In this project it model the problem in terms of semantic segmentation and approach it by means of deep learning, and more specifically with the U-Net architecture.

This project presents a coin counter system based on Convolutional Neural Networks (CNNs) and Digital Image Processing techniques. The framework's uses images taken by a cellphone camera as input and output the quantity of coins and the amount of money. Note: it should be noted that the system has been tests ONLY on Colombian coins.