12-01, 22:30–23:00 (UTC), Talk Track II
KerasCV offers a complete set of APIs to train your own state-of-the-art,
production-grade object detection model. These APIs include object detection specific
data augmentation techniques, models, and COCO metrics.
This talk covers how to train a RetinaNet on your own dataset using KerasCV
KerasCV offers a complete set of APIs to train your own state-of-the-art,
production-grade object detection model. These APIs include object detection specific
data augmentation techniques, models, and COCO metrics.
This talk covers how to train a RetinaNet on your own dataset using KerasCV
No previous knowledge expected
Luke Wood is a Machine Learning Specialist and a Software Engineering Generalist. Currently, Luke's focuses are in making KerasCV a powerful and expressive library to solve common Computer Vision tasks and publishing high quality research in top Machine Learning conferences. Luke currently works full time at Google on the Keras team, and is pursuing his Doctorate in Machine Learning at UC San Diego under Peter Gerstoft.