Explore object detection with transformers in this comprehensive 32-minute talk from Databricks. Learn the fundamentals of object detection, including key concepts and techniques, before delving into cutting-edge methods that utilize transformers to streamline the detection pipeline. Discover the main ideas behind DETR and Deformable DETR approaches, and gain an overview of Determined AI's deep learning platform capabilities, focusing on effortless distributed training. Master the process of training object detection models at scale and serving them using MLflow. Grasp essential topics such as mean average precision, transformer decoder architecture, positional encoding, and deformable attention. Follow along as the speaker demonstrates defining PyTorch trials, configuring experiments, and utilizing Determined's web UI for hyperparameter search, automatic fault tolerance, and model saving. By the end of this talk, acquire the knowledge to implement advanced object detection techniques and deploy them effectively in various applications, from medical image analysis to autonomous driving.
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Object Detection with Transformers - From Training to Deployment