Collaborating Authors

Developing emotion recognition for video conference software to support people with autism Artificial Intelligence

We develop an emotion recognition software for the use with a video conference software for autistic individuals which are unable to recognize emotions properly. It can get an image out of the video stream, detect the emotion in it with the help of a neural network and display the prediction to the user. The network is trained on facial landmark features. The software is fully modular to support adaption to different video conference software, programming languages and implementations.

OCR with Keras, TensorFlow, and Deep Learning - PyImageSearch


In this tutorial, you will learn how to train an Optical Character Recognition (OCR) model using Keras, TensorFlow, and Deep Learning. For now, we'll primarily be focusing on how to train a custom Keras/TensorFlow model to recognize alphanumeric characters (i.e., the digits 0-9 and the letters A-Z). Building on today's post, next week we'll learn how we can use this model to correctly classify handwritten characters in custom input images. We'll be starting with the fundamentals of using well-known handwriting datasets and training a ResNet deep learning model on these data. To learn how to train an OCR model with Keras, TensorFlow, and deep learning, just keep reading.

TensorFlow 2 Tutorial: Get Started in Deep Learning With tf.keras


You can easily create learning curves for your deep learning models. First, you must update your call to the fit function to include reference to a validation dataset. This is a portion of the training set not used to fit the model, and is instead used to evaluate the performance of the model during training.

Develop Your First Neural Network in Python With Keras Step-By-Step


Keras is a powerful easy-to-use Python library for developing and evaluating deep learning models. It wraps the efficient numerical computation libraries Theano and TensorFlow and allows you to define and train neural network models in a few short lines of code. In this post you will discover how to create your first neural network model in Python using Keras. Develop Your First Neural Network in Python With Keras Step-By-Step Photo by Phil Whitehouse, some rights reserved. There is not a lot of code required, but we are going to step over it slowly so that you will know how to create your own models in the future.

Transfer Learning with TensorFlow 2


It is always fun and educational to read deep learning scientific papers. Especially if it is in the area of the current project that you are working on. However, often these papers contain architectures and solutions that are hard to train. Especially if you want to try out, let's say, some of the winners of ImageNet Large Scale Visual Recognition (ILSCVR) competition. I can remember reading about VGG16 and thinking "That is all cool, but my GPU is going to die".