Skip to Main Content
Hands-On Java Deep Learning for Computer Vision
book

Hands-On Java Deep Learning for Computer Vision

by Klevis Ramo
February 2019
Intermediate to advanced content levelIntermediate to advanced
260 pages
6h 3m
English
Packt Publishing
Content preview from Hands-On Java Deep Learning for Computer Vision

Building a handwritten digit recognizer

By building a handwritten digit recognizer in a Java application, we will practically implement most of the techniques and optimizations learned so far. The application is built using the open source Java framework, Deeplearning4j. The dataset used is the classic MNIST database of handwritten digits. (http://yann.lecun.com/exdb/mnist/). The training dataset is oversized, having 60,000 images, while the test data set contains 10,000 images. The images are 28 x 28 in size and grayscale in terms of terms.

As a part of the application that we will be creating in this section, we will implement a graphical user interface, where you can draw digits and get a neural network to recognize the digit.

Jumping ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Java Deep Learning Projects

Java Deep Learning Projects

Md. Rezaul Karim
Hands-On Computer Vision with TensorFlow 2

Hands-On Computer Vision with TensorFlow 2

Benjamin Planche, Eliot Andres

Publisher Resources

ISBN: 9781789613964Supplemental Content