Invention Grant
- Patent Title: Deep-learning models for image processing
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Application No.: US17618208Application Date: 2020-06-12
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Publication No.: US12079991B2Publication Date: 2024-09-03
- Inventor: John Galeotti , Tejas Sudharshan Mathai
- Applicant: Carnegie Mellon University
- Applicant Address: US PA Pittsburgh
- Assignee: Carnegie Mellon University
- Current Assignee: Carnegie Mellon University
- Current Assignee Address: US PA Pittsburgh
- Agency: The Webb Law Firm
- International Application: PCT/US2020/037427 2020.06.12
- International Announcement: WO2020/252256A 2020.12.17
- Date entered country: 2021-12-10
- Main IPC: G06T7/00
- IPC: G06T7/00 ; G06N3/045 ; G06N3/082 ; G06T7/11

Abstract:
Provided is a system, method, and computer program product for creating a deep-learning model for processing image data. The method includes establishing dense connections between each layer of a plurality of layers of a convolutional neural network (CNN) and a plurality of preceding layers of the CNN, downsampling an input of each downsampling layer of a plurality of downsampling layers in a first branch of the CNN, and upsampling an input of each upsampling layer of a plurality of upsampling layers in a second branch of the CNN by convolving the input.
Public/Granted literature
- US20220172360A1 Deep-Learning Models for Image Processing Public/Granted day:2022-06-02
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