Convolutional Networks in Java - Deeplearning4j: Open-source, Distributed Deep Learning for the JVM

Convolutional nets can be used to classify images (name what they see), cluster them by similarity (photo search), and perform object recognition within scenes. They can identify faces, individuals, street signs, eggplants, platypuses and many other aspects of visual data. Convolutional nets overlap with text analysis via optical character recognition (OCR), where the images are symbols to be transcribed, and they can also be applied to sound when it is represented visually. The efficacy of convolutional nets (ConvNets or CNNs) in image recognition is one of the main reasons why the world has woken up to deep learning. They are powering major advances in machine vision, which has obvious applications for self-driving cars, robotics, drones, and treatments for the visually impaired.