Invention Grant
- Patent Title: Training and/or using neural network models to generate intermediary output of a spectral image
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Application No.: US16406540Application Date: 2019-05-08
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Publication No.: US11138470B2Publication Date: 2021-10-05
- Inventor: Alexander Gorban
- Applicant: GOOGLE LLC
- Applicant Address: US CA Mountain View
- Assignee: GOOGLE LLC
- Current Assignee: GOOGLE LLC
- Current Assignee Address: US CA Mountain View
- Agency: Middleton Reutlinger
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06N3/04 ; G06K9/66

Abstract:
Systems, methods, and computer readable media related to training and/or using a neural network model. The trained neural network model can be utilized to generate (e.g., over a hidden layer) a spectral image based on a regular image, and to generate output indicative of one or more features present in the generated spectral image (and present in the regular image since the spectral image is generated based on the regular image). As one example, a regular image may be applied as input to the trained neural network model, a spectral image generated over multiple layers of the trained neural network model based on the regular image, and output generated over a plurality of additional layers based on the spectral image. The generated output may be indicative of various features, depending on the training of the additional layers of the trained neural network model.
Public/Granted literature
- US20190266446A1 TRAINING AND/OR USING NEURAL NETWORK MODELS TO GENERATE INTERMEDIARY OUTPUT OF A SPECTRAL IMAGE Public/Granted day:2019-08-29
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