Invention Grant
- Patent Title: Semantic segmentation ground truth correction with spatial transformer networks
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Application No.: US17110693Application Date: 2020-12-03
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Publication No.: US11699234B2Publication Date: 2023-07-11
- Inventor: Ian Endres
- Applicant: HERE Global B.V.
- Applicant Address: NL Eindhoven
- Assignee: HERE GLOBAL B.V.
- Current Assignee: HERE GLOBAL B.V.
- Current Assignee Address: NL Eindhoven
- Agency: Here Global B.V.
- Agent Jason Wejnert
- Main IPC: G06T7/10
- IPC: G06T7/10 ; G06N3/08 ; G06N3/047

Abstract:
An apparatus accesses label data and training images corresponding to a geographic area; and provides the label data and training images to a training model. The training model comprises of at least a predictor model and an alignment model. The predictor model is configured to receive an image and provide a prediction corresponding to the image. The alignment model is configured to generate a transformed prediction based on aligning the label data and the prediction. The apparatus executes a loss engine to iteratively receive the label data and the transformed prediction, evaluate a loss function based on the label data and the transformed prediction, and cause weights of the predictor model and the alignment model to be updated based on the evaluated loss function to cause the predictor and alignment models to be trained.
Public/Granted literature
- US20210383544A1 SEMANTIC SEGMENTATION GROUND TRUTH CORRECTION WITH SPATIAL TRANSFORMER NETWORKS Public/Granted day:2021-12-09
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