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1. (WO2018063460) SYSTEM AND METHOD FOR OPTIMIZATION OF DEEP LEARNING ARCHITECTURE
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Pub. No.: WO/2018/063460 International Application No.: PCT/US2017/038504
Publication Date: 05.04.2018 International Filing Date: 21.06.2017
IPC:
G06N 3/04 (2006.01) ,G06K 9/46 (2006.01)
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
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
36
Image preprocessing, i.e. processing the image information without deciding about the identity of the image
46
Extraction of features or characteristics of the image
Applicants:
GENERAL ELECTRIC COMPANY [US/US]; 1 River Road Schenectady, New York 12345, US
Inventors:
THIRUVENKADAM, Sheshadri; IN
RANJAN, Sohan Rashmi; IN
VAIDYA, Vivek Prabhakar; IN
RAVISHANKAR, Hariharan; IN
VENKATARAMANI, Rahul; IN
SUDHAKAR, Prasad; IN
Agent:
DIVINE, Lucas; US
DEVINS, Elizabeth; US
GROETHE, Jacob; US
VIVENZIO, Marc; US
BAXTER, William; US
TOPPIN, Catherine; US
Priority Data:
20164103361830.09.2016IN
Title (EN) SYSTEM AND METHOD FOR OPTIMIZATION OF DEEP LEARNING ARCHITECTURE
(FR) SYSTÈME ET PROCÉDÉ D'OPTIMISATION D'UNE ARCHITECTURE D'APPRENTISSAGE EN PROFONDEUR
Abstract:
(EN) A method for determining optimized deep learning architecture includes receiving a plurality of training images and a plurality of real time images corresponding to a subject. The method further includes receiving, by a medical practitioner, a plurality of learning parameters comprising a plurality of filter classes and a plurality of architecture parameters. The method also includes determining a deep learning model based on the plurality of learning parameters and the plurality of training images, wherein the deep learning model comprises a plurality of reusable filters. The method further includes determining a health condition of the subject based on the plurality of real time images and the deep learning model. The method also includes providing the health condition of the subject to the medical practitioner.
(FR) Selon la présente invention, un procédé permettant de déterminer une architecture d'apprentissage en profondeur optimisée consiste à recevoir une pluralité d'images d'apprentissage et une pluralité d'images en temps réel correspondant à un sujet. Le procédé consiste en outre en la réception, par un praticien, d'une pluralité de paramètres d'apprentissage comprenant une pluralité de classes de filtres et une pluralité de paramètres d'architecture. Le procédé consiste également à déterminer un modèle d'apprentissage en profondeur sur la base de la pluralité de paramètres d'apprentissage et de la pluralité d'images d'apprentissage, le modèle d'apprentissage en profondeur comprenant une pluralité de filtres réutilisables. Le procédé consiste en outre à déterminer une condition de santé du sujet sur la base de la pluralité d'images en temps réel et du modèle d'apprentissage en profondeur. Le procédé consiste également à fournir l'état de santé du sujet au praticien.
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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 Office (AM, AZ, BY, KG, KZ, RU, TJ, TM)
European Patent Office (EPO) (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)