Invention Grant
- Patent Title: Efficient convolutional neural networks and techniques to reduce associated computational costs
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Application No.: US16668303Application Date: 2019-10-30
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Publication No.: US11449714B2Publication Date: 2022-09-20
- Inventor: Valentin Bazarevsky , Yury Kartynnik , Andrei Vakunov , Karthik Raveendran , Matthias Grundmann
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Dority & Manning, P.A.
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06K9/62 ; G06N3/04 ; G06N3/08 ; G06V40/16

Abstract:
A computing system is disclosed including a convolutional neural configured to receive an input that describes a facial image and generate a facial object recognition output that describes one or more facial feature locations with respect to the facial image. The convolutional neural network can include a plurality of convolutional blocks. At least one of the convolutional blocks can include one or more separable convolutional layers configured to apply a depthwise convolution and a pointwise convolution during processing of an input to generate an output. The depthwise convolution can be applied with a kernel size that is greater than 3×3. At least one of the convolutional blocks can include a residual shortcut connection from its input to its output.
Public/Granted literature
- US20210133508A1 Efficient Convolutional Neural Networks and Techniques to Reduce Associated Computational Costs Public/Granted day:2021-05-06
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