公开(公告)号：US10943154B2

公开(公告)日：2021-03-09

申请号：US16254439

申请日：2019-01-22

Applicant: HONDA MOTOR CO., LTD.

Inventor： Ahmed Taha ,  Yi-Ting Chen ,  Teruhisa Misu ,  Larry Davis ,  Xitong Yang

IPC: G06K9/62 ,  G06N3/08 ,  G06K9/00

Abstract: Multi-modal data representing driving events and corresponding actions related to the driving events can be obtained and used to train a neural network at least in part by using a triplet loss computed for the driving events as a regression loss to determine an embedding of driving event data. In some cases, using the trained neural network, a retrieval request for an input driving event and corresponding action can be processed by determining, from the neural network, one or more similar driving events or corresponding actions in the multi-modal data.

公开(公告)号：US10902303B2

公开(公告)日：2021-01-26

申请号：US16254344

申请日：2019-01-22

Applicant: HONDA MOTOR CO., LTD.

Inventor： Ahmed Taha ,  Yi-Ting Chen ,  Teruhisa Misu ,  Larry Davis

IPC: G06K9/66 ,  G06K9/00 ,  G06N3/08 ,  G06K9/62

Abstract: Methods, systems, and computer-readable mediums storing computer executable code for visual recognition implementing a triplet loss function are provided. The method include receiving an image generated from an image source associated with a vehicle. The method may also include analyzing the image based on a convolutional neural network. The convolutional neural network may apply both a triplet loss function and a softmax loss function to the image to determine classification logits. The method may also include classifying the image into a predetermined class distribution based upon the determined classification logits. The method may also include instructing the vehicle to perform a specific task based upon the classified image.