The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 14, 2025

Filed:

Feb. 19, 2021
Applicant:

Illumina, Inc., San Diego, CA (US);

Inventors:

Anindita Dutta, San Francisco, CA (US);

Gery Vessere, Oakland, CA (US);

Dorna Kashefhaghighi, Menlo Park, CA (US);

Gavin Derek Parnaby, Laguna Niguel, CA (US);

Kishore Jaganathan, San Francisco, CA (US);

Amirali Kia, San Mateo, CA (US);

Assignee:

Illumina, Inc., San Diego, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06V 10/82 (2022.01); C12Q 1/6869 (2018.01); G06F 18/23 (2023.01); G06N 3/063 (2023.01); G06N 3/084 (2023.01); G06V 10/44 (2022.01); G06V 10/762 (2022.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G16B 30/20 (2019.01);
U.S. Cl.
CPC ...
G06N 3/084 (2013.01); G06F 18/23 (2023.01); G06N 3/063 (2013.01); G06V 10/454 (2022.01); G06V 10/762 (2022.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/82 (2022.01); G16B 30/20 (2019.02); C12Q 1/6869 (2013.01);
Abstract

The technology disclosed relates to a system that comprises a spatial convolution network and a temporal convolution network. The spatial convolution network is configured to process a window of per-cycle sequencing image sets and generate respective per-cycle spatial feature map sets. Trained coefficients of spatial convolution filters in spatial convolution filter banks of respective sequences of spatial convolution filter banks vary between sequences of spatial convolution layers in respective sequences of spatial convolution layers. The temporal convolution network is configured to process the per-cycle spatial feature map sets on a groupwise basis and generate respective per-group temporal feature map sets. Trained coefficients of temporal convolution filters in respective temporal convolution filter banks vary between temporal convolution filter banks in respective temporal convolution filter banks.


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