Pilas de combustible

ADAPTIVELY TRAINING OF NEURAL NETWORKS VIA AN INTELLIGENT LEARNING MANAGEMENT SYSTEM

Resumen de: US2025307604A1

Computer systems and computer-implemented methods train a neural network, by:(a) computing for each datum in a set of training data, activation values for nodes in the neural network and estimates of partial derivatives of an objective function for the neural network for the nodes in the neural network; (b) selecting a target node of the neural network and/or a target datum in the set of training data; (c) selecting a target-specific improvement model for the neural network, wherein the target-specific improvement model, when added to the neural network, improves performance of the neural network for the target node and/or the target datum, as the case may be; (d) training the target-specific improvement model; (e) merging the target-specific improvement model with the neural network to form an expanded neural network; and (f) training the expanded neural network.

END-TO-END DETECTION OF REDUCED DRIVABILITY AREAS IN AUTONOMOUS VEHICLE APPLICATIONS

Nº publicación: US2025305834A1 02/10/2025

Solicitante:

WAYMO LLC [US]
Waymo LLC

Resumen de: US2025305834A1

The disclosed systems and techniques facilitate efficient detection and navigation of reduced drivability areas in driving environments. The disclosed techniques include, obtaining, using a sensing system of a vehicle, a set of camera images, a set of radar images, and/or a set of lidar images of an environment. The techniques further include generating, using a first neural network (NN), camera feature(s) characterizing the camera images, generating, using a second NN, radar features characterizing the radar images, and/or generating, using a third NN, lidar feature(s) characterizing the lidar images. The techniques further include processing the camera feature(s), the radar feature(s), and the lidar feature(s) to obtain an indication of a reduced drivability area in the environment.