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1. (WO2019032421) IMPROVED TECHNIQUE FOR MACHINE VISUAL LEARNING
Latest bibliographic data on file with the International BureauSubmit observation

Pub. No.: WO/2019/032421 International Application No.: PCT/US2018/045311
Publication Date: 14.02.2019 International Filing Date: 06.08.2018
IPC:
G06K 9/62 (2006.01) ,G06K 9/66 (2006.01) ,G06K 9/00 (2006.01) ,G06N 3/08 (2006.01) ,G06N 3/04 (2006.01)
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
K
RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9
Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
62
Methods or arrangements for recognition using electronic means
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
K
RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9
Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
62
Methods or arrangements for recognition using electronic means
64
using simultaneous comparisons or correlations of the image signals with a plurality of references, e.g. resistor matrix
66
references adjustable by an adaptive method, e.g. learning
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
K
RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9
Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
N
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3
Computer systems based on biological models
02
using neural network models
08
Learning methods
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
N
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3
Computer systems based on biological models
02
using neural network models
04
Architecture, e.g. interconnection topology
Applicants:
SIEMENS AKTIENGESELLSCHAFT [DE/DE]; Werner-von-Siemens-Straße 1 80333 München, DE
SIEMENS CORPORATION [US/US]; 170 Wood Avenue South Iselin, New Jersey 08830, US (BW, GH, GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, UG, ZM, ZW)
Inventors:
GONG, Yunye; US
WU, Ziyan; US
ERNST, Jan; US
Agent:
OTTERLEE, Thomas J.; US
Priority Data:
62/541,93607.08.2017US
62/632,00219.02.2018US
Title (EN) IMPROVED TECHNIQUE FOR MACHINE VISUAL LEARNING
(FR) TECHNIQUE AMÉLIORÉE D'APPRENTISSAGE VISUEL MACHINE
Abstract:
(EN) A method of expanding a visual learning database in a computer by teaching the computer includes providing a series of training images to the computer wherein each series includes three images with each image falling within a unique image domain and with each image domain representing a possible combination of a first attribute and a second attribute with a first image domain including the first attribute and the second attribute in a first state (X=0, Y=0), a second image domain including the first attribute in a second state and the second attribute in the first state (X=1, Y=0), and a third image domain including the first attribute in the first state and the second attribute in the second state (X=0, Y=1). The method also includes developing within the computer forward generators and reverse generators between the first image domain, the second image domain, the third image domain, and a fourth image domain for which no training image is provided, and applying with the computer the forward generators and reverse generators to single images that fall within one of the first image domain, the second image domain, the third image domain, and a fourth image domain to generate images for the remaining domains to populate a database.
(FR) L’invention concerne un procédé d'extension d'une base de données d'apprentissage visuel dans un ordinateur par apprentissage de l'ordinateur qui consiste à fournir une série d'images d'apprentissage à l'ordinateur, chaque série comprenant trois images, chaque image tombant dans un domaine d'image unique et chaque domaine d'image représentant une combinaison possible d'un premier attribut et d'un second attribut avec un premier domaine d'image comprenant le premier attribut et le second attribut dans un premier état (X = 0, Y = 0), un deuxième domaine d'image comprenant le premier attribut dans un second état et le second attribut dans le premier état (X = 1, Y = 0), et un troisième domaine d'image comprenant le premier attribut dans le premier état et le second attribut dans le second état (X = 0, Y = 1). Le procédé comprend également le développement dans les générateurs vers l'avant et dans les générateurs inverses de l'ordinateur entre le premier domaine d'image, le deuxième domaine d'image, le troisième domaine d'image et un quatrième domaine d'image pour lequel aucune image d'apprentissage n'est fournie, et l'application des générateurs vers l'avant et les générateurs inverses de l'ordinateur à des images simples qui tombent dans l'un des premier, deuxième, troisième et quatrième domaine d'image pour générer des images pour les domaines restants afin d'alimenter une base de données.
front page image
Designated States: AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW
African Regional Intellectual Property Organization (ARIPO) (BW, GH, GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, UG, ZM, ZW)
Eurasian Patent Organization (AM, AZ, BY, KG, KZ, RU, TJ, TM)
European Patent Office (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR)
African Intellectual Property Organization (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, KM, ML, MR, NE, SN, TD, TG)
Publication Language: English (EN)
Filing Language: English (EN)