Evan Juras, Computer Vision Engineer at EJ Technology Consultants, presents the “Practical Image Data Augmentation Methods for Training Deep Learning Object Detection Models” tutorial at the September 2020 Embedded Vision Summit.
Data augmentation is a method of expanding deep learning training datasets by making various automated modifications to existing images in the dataset. The resulting increased data diversity can enable a more accurate and robust model without the need to manually obtain more images.
In this presentation, Juras explores practical methods of image data augmentation for training object detection models. He also shows how to create an augmented dataset of 50,000 unique images with labeled bounding boxes in a few hours using a short Python script.
See here for a PDF of the slides.
