Invention Grant
- Patent Title: Skip architecture neural network machine and method for improved semantic segmentation
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Application No.: US15798349Application Date: 2017-10-30
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Publication No.: US10410350B2Publication Date: 2019-09-10
- Inventor: Jiu Xu , Bjorn Stenger
- Applicant: Rakuten, Inc.
- Applicant Address: JP Tokyo
- Assignee: Rakuten, Inc.
- Current Assignee: Rakuten, Inc.
- Current Assignee Address: JP Tokyo
- Agency: HEA Law PLLC
- Main IPC: G06T7/11
- IPC: G06T7/11 ; G06K9/66 ; G06N7/00 ; G06N3/08

Abstract:
A method of using a computer to semantically segment an image using a convolutional neural network system where a processor configured to convolve an input image with a plurality of filters and outputting a first output volume, pool the first output volume and creating a first activation map, determine the level of influence of the first activation map on the semantic segmentation, up-pool the first activation map to form an output image having a same number of pixels as the input image, output a probabilistic segmentation result, labeling each pixel's probability that it is a particular label, and the determination of the level of influence of the first activation map on the semantic segmentation is done using a gate layer that is positioned between a pooling layer and an up-pooling layer.
Public/Granted literature
- US20190130573A1 SKIP ARCHITECTURE NEURAL NETWORK MACHINE AND METHOD FOR IMPROVED SEMANTIC SEGMENTATION Public/Granted day:2019-05-02
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