Ford Global Technolgoies, LLC

Armin Parchami

Faizan Shaik

Enrique Corona

Ghassan AlRegib

Mohit Prabhushankar

Dogancan Temel

Gukyeong Kwon

Neural networks and learning algorithms can use a variance of gradients to provide a heuristic understanding of the model. The variance of gradients can be used in active learning techniques to train a neural network. Techniques include receiving a dataset with a vector. The dataset can be annotated and a loss calculated. The loss value can be used to update the neural network through backpropagation. An updated dataset can be used to calculate additional losses. The loss values can be added to a pool of gradients. A variance of gradients can be calculated from the pool of gradient vectors. The variance of gradients can be used to update a neural network.

Variance of gradient based active learning framework for training perception algorithms

A system, including a processor and a memory, the memory including instructions to be executed by the processor to determine camera calibration parameters including camera focal distance, camera height and camera tilt based on a two-dimensional calibration pattern located parallel to and coincident with a ground plane determined by a roadway surface and determine object data including object location, object speed and object direction for one or more objects in a field of view of the video camera.

Traffic camera calibration

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Ann Arbor, MI, United States of America

Armin Parchami