Invention Application
- Patent Title: Noise Tolerant Ensemble RCNN for Semi-Supervised Object Detection
-
Application No.: US17437238Application Date: 2019-03-08
-
Publication No.: US20220172456A1Publication Date: 2022-06-02
- Inventor: Jiang Wang , Jiyang Gao , Shengyang Dai
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- International Application: PCT/US2019/021375 WO 20190308
- Main IPC: G06V10/764
- IPC: G06V10/764 ; G06V10/84 ; G06V10/20

Abstract:
The present disclosure provides systems and methods that include or otherwise leverage an object detection training model for training a machine-learned object detection model. In particular, the training model can obtain first training data and train the machine-learned object detection model using the first training data. The training model can obtain second training data and input the second training data into the machine-learned object detection model, and receive as an output of the machine-learned object detection model, data that describes the location of a detected object of a target category within images from the second training data. The training model can determine mined training data based on the output of the machine-learned object detection model, and train the machine-learned object detection model based on the mined training data.
Information query