US 12,443,838 B2
Diffractive deep neural networks with differential and class-specific detection
Aydogan Ozcan, Sherman Oaks, CA (US); Yair Rivenson, Los Angeles, CA (US); Jingxi Li, Los Angeles, CA (US); Deniz Mengu, Los Angeles, CA (US); and Yi Luo, Los Angeles, CA (US)
Assigned to THE REGENTS OF THE UNIVERSITY OF CALIFORNIA, Oakland, CA (US)
Appl. No. 17/616,983
Filed by THE REGENTS OF THE UNIVERSITY OF CALIFORNIA, Oakland, CA (US)
PCT Filed Jun. 5, 2020, PCT No. PCT/US2020/036436
§ 371(c)(1), (2) Date Dec. 6, 2021,
PCT Pub. No. WO2020/247828, PCT Pub. Date Dec. 10, 2020.
Claims priority of provisional application 62/858,799, filed on Jun. 7, 2019.
Prior Publication US 2022/0327371 A1, Oct. 13, 2022
Int. Cl. G06N 3/067 (2006.01); G02B 27/42 (2006.01); G06N 3/08 (2023.01); G06N 20/00 (2019.01)
CPC G06N 3/0675 (2013.01) [G02B 27/4277 (2013.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01)] 23 Claims
OG exemplary drawing
 
1. A diffractive optical neural network device for machine learning, classification, and/or processing of at least one optical image, signal, or data comprising:
a plurality of optically transmissive and/or reflective substrate layers arranged in one or more optical paths, each of the plurality of optically transmissive and/or reflective substrate layers comprising a plurality of physical features formed on or within the optically transmissive and/or reflective substrate layers and having different complex-valued transmission and/or reflection coefficients as a function of lateral coordinates across each substrate layer, wherein the plurality of optically transmissive and/or reflective substrate layers and the plurality of physical features thereon collectively define a trained mapping function between an input optical image, input optical signal, or input data to the plurality of optically transmissive and/or reflective substrate layers and one or more output optical images, output optical signals, or data created by optical diffraction/reflection through/off the plurality of optically transmissive and/or reflective substrate layers;
a plurality of groups of optical sensors configured to sense and detect the output optical images, output optical signals, or data resulting from the plurality of optically transmissive and/or reflective substrate layers, wherein each group of optical sensors comprises at least one optical sensor configured to capture a positive signal from the output optical images, output optical signals, or data and at least one optical sensor configured to capture a negative signal from the output optical images, output optical signals, or data; and
circuitry and/or computer software configured to identify a group of optical sensors within the plurality of groups of optical sensors in which a normalized signal difference calculated from the positive and negative optical sensors within each group that has a largest or a smallest normalized signal difference of among all the groups.