Patent ID: 11887381
Assignee: NEW EAGLE, LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G  B | IPC B  G

Claim 17:
18. A method of predicting lane line types utilizing a heterogeneous convolutional neural network (HCNN), the method comprising:
capturing an input image with one or more optical sensors disposed on a host member;
passing the input image through four shared convolution and pooling convolutional layer portions (CPLs) within the HCNN, the HCNN having at least three distinct sub-networks; and
passing an output of the four shared convolutional layers through at least three fully connected layers within the HCNN;
training a first sub-network by minimizing a loss function of the first sub-network while freezing a second sub-network and a third sub-network;
training the second sub-network by minimizing a loss function of the second sub-network while freezing the first sub-network and the third sub-network; and
training the third sub-network by minimizing a loss function of the third sub-network while freezing the first sub-network and the second sub-network, and
wherein the first sub-network performs a first task of object detection, classification, and localization for classes of objects in the input image to create a detected object table, the second sub-network performs a second task of lane line detection and localization for classes of lane lines in the input image to create a lane line location table, and the third sub-network performs a third task of lane line type detection for classes of lane lines types in the input image and creates a detected lane line type table.