Invention Application
- Patent Title: OPTIMIZED POLICY-BASED ACTIVE LEARNING FOR CONTENT DETECTION
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Application No.: US17170307Application Date: 2021-02-08
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Publication No.: US20220253630A1Publication Date: 2022-08-11
- Inventor: Sumit Shekhar , Bhanu Prakash Reddy Guda , Ashutosh Chaubey , Ishan Jindal , Avneet Jain
- Applicant: ADOBE INC.
- Applicant Address: US CA SAN JOSE
- Assignee: ADOBE INC.
- Current Assignee: ADOBE INC.
- Current Assignee Address: US CA SAN JOSE
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06K9/62 ; G06N20/00

Abstract:
Systems and methods for training an object detection network are described. Embodiments train an object detection network using a labeled training set, wherein each element of the labeled training set includes an image and ground truth labels for object instances in the image, predict annotation data for a candidate set of unlabeled data using the object detection network, select a sample image from the candidate set using a policy network, generate a labeled sample based on the selected sample image and the annotation data, wherein the labeled sample includes labels for a plurality of object instances in the sample image, and perform additional training on the object detection network based at least in part on the labeled sample.
Public/Granted literature
- US11948387B2 Optimized policy-based active learning for content detection Public/Granted day:2024-04-02
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