Deep Learning for Computer Vision using Python and MATLAB

Deep Learning (DL) techniques have changed the field of computer vision significantly during the last decade, providing state-of-the-art solutions for classical tasks (e.g., object detection and image classification) and opening the doors for solving challenging new problems, such as image-to-image translation and visual question answering (VQA). The success and popularization of DL in computer vision and related areas (e.g., medical image analysis) has been fostered, in great part, by the availability of rich tools, apps and frameworks in the Python and MATLAB ecosystems. In this blog post, I will show how your team can use both MATLAB and Python effectively and provide an easy-to-follow recipe that you should allow you to leverage "the best of both worlds" when building computer vision solutions using deep learning. Python is a programming language created by Guido van Rossum in the early 1990s. It has been adopted by many data scientists and machine/deep learning researchers thanks to popular packages (e.g., scikit-learn) and frameworks (e.g., Keras, TensorFlow, PyTorch).