US 12,131,454 B2
Substrate mapping using deep neural-networks
Jason Paul Remillard, Groton, MA (US); John D. Nevin, IV, Andover, MN (US); and Stephen W. Into, Harvard, MA (US)
Assigned to Onto Innovation, Inc., Wilmington, MA (US)
Filed by Onto Innovation, Inc., Wilmington, MA (US)
Filed on Sep. 15, 2021, as Appl. No. 17/476,195.
Prior Publication US 2023/0085039 A1, Mar. 16, 2023
Int. Cl. G06T 7/00 (2017.01); B25J 9/16 (2006.01); G06F 18/24 (2023.01); H01L 21/677 (2006.01)
CPC G06T 7/0004 (2013.01) [B25J 9/1697 (2013.01); G06F 18/24 (2023.01); H01L 21/67766 (2013.01); H01L 21/67769 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for classifying a state of a plurality of substrates for a plurality of locations in a substrate carrier, the method comprising:
detecting at least a portion of the plurality of substrates in the substrate carrier, the detecting including capturing one or more images of the portion of the plurality of substrates for the plurality of locations that is proximate to the portion of the plurality of substrates;
sending the one or more images to a pre-trained deep-convolutional neural-network;
classifying the state of the portion of the plurality of substrates for the plurality of locations within the substrate carrier from the one or more images using the pre-trained deep-convolutional neural-network; and
using the state of the portion of the plurality of substrates to set how a substrate of the plurality of substrates within the substrate carrier is handled.