Train-time loss in a system and method for calibrating object detection

Abstract

A system and method of training a deep neural network for object detection in an object detection system. The object detection system including a camera and a controller including the DNN. The method including capturing an image by the camera, receiving the image, predicting, using the DNN, a bounding box and corresponding class label, evaluating the prediction with a total loss function including an object detection loss function, a box regression loss function, and a calibration loss function that takes into account precision and confidence. The method outputs a calibrated image with the object bounding box, the corresponding label, and a respective confidence score, in which the confidence score is a probability associated with the predicted class label.