Processing

Please wait...

Settings

Settings

Goto Application

1. WO2022136180 - COMPUTER-IMPLEMENTED METHODS FOR TRAINING A NEURAL NETWORK DEVICE AND CORRESPONDING METHODS FOR GENERATING A FRAGRANCE OR FLAVOR COMPOSITIONS

Publication Number WO/2022/136180
Publication Date 30.06.2022
International Application No. PCT/EP2021/086591
International Filing Date 17.12.2021
IPC
G16C 60/00 2019.1
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
60Computational materials science, i.e. ICT specially adapted for investigating the physical or chemical properties of materials or phenomena associated with their design, synthesis, processing, characterisation or utilisation
G16C 20/30 2019.1
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
20Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
30Prediction of properties of chemical compounds, compositions or mixtures
G16C 20/70 2019.1
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
20Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
70Machine learning, data mining or chemometrics
G06N 3/04 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architecture, e.g. interconnection topology
CPC
C11B 9/00
CCHEMISTRY; METALLURGY
11ANIMAL OR VEGETABLE OILS, FATS, FATTY SUBSTANCES OR WAXES; FATTY ACIDS THEREFROM; DETERGENTS; CANDLES
BPRODUCING, e.g. BY PRESSING RAW MATERIALS OR BY EXTRACTION FROM WASTE MATERIALS, REFINING OR PRESERVING FATS, FATTY SUBSTANCES, e.g. LANOLIN, FATTY OILS OR WAXES; ESSENTIAL OILS; PERFUMES
9Essential oils; Perfumes
G01N 33/0027
GPHYSICS
01MEASURING; TESTING
NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
33Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
0004Gaseous mixtures, e.g. polluted air
0009General constructional details of gas analysers, e.g. portable test equipment
0027concerning the detector
G06K 9/6257
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
62Methods or arrangements for recognition using electronic means
6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
6256Obtaining sets of training patterns; Bootstrap methods, e.g. bagging, boosting
6257characterised by the organisation or the structure of the process, e.g. boosting cascade
G06N 20/20
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
20Machine learning
20Ensemble learning
G06N 3/0454
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architectures, e.g. interconnection topology
0454using a combination of multiple neural nets
G06N 3/0472
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architectures, e.g. interconnection topology
0472using probabilistic elements, e.g. p-rams, stochastic processors
Applicants
  • FIRMENICH SA [CH]/[CH]
Inventors
  • GODIN, Guillaume
  • VAN DEURSEN, Ruud
  • NOUCHI, Vincent
  • CAPELA, Fabio André
  • RAMET, Gaétan
  • CALVAYRAC, Thibault
  • CHICHESTER, Christine
Agents
  • LAVY, Séverine
Priority Data
20216123.821.12.2020EP
21170833.428.04.2021EP
Publication Language English (en)
Filing Language English (EN)
Designated States
Title
(EN) COMPUTER-IMPLEMENTED METHODS FOR TRAINING A NEURAL NETWORK DEVICE AND CORRESPONDING METHODS FOR GENERATING A FRAGRANCE OR FLAVOR COMPOSITIONS
(FR) PROCÉDÉS MIS EN ŒUVRE PAR ORDINATEUR POUR ENTRAINER UN DISPOSITIF DE RÉSEAU NEURONAL ET PROCÉDÉS CORRESPONDANTS POUR GÉNÉRER DES COMPOSITIONS DE PARFUM OU D'ARÔME
Abstract
(EN) The computer-implemented method (100) for training an autoencoder neural network or generative adversarial network device to generate indeterministic and realistic digital representations of new fragrance or flavor ingredient compositions to be compounded, comprises the steps of: - providing (105) an original set of exemplar fragrance or flavor composition digital identifiers, said exemplar fragrance or flavor composition digital identifiers being representative of materialized fragrance or flavor compositions comprising at least two distinct ingredients and - training (110) an autoencoder device or generative adversarial network device using the original set of exemplar fragrance or flavor composition digital identifiers to generate a fragrance or flavor composition generative model trained to generate new fragrance or flavor ingredient compositions, comprising at least two distinct ingredients, to be compounded. The trained autoencoder device or generative adversarial network device can be used to generate new fragrance or flavor ingredient compositions.
(FR) La présente invention concerne un procédé mis en œuvre par ordinateur (100) pour entrainer un dispositif de réseau neuronal autocodeur ou de réseau antagoniste génératif pour générer des représentations numériques indéterministes et réalistes de nouvelles compositions à base d'ingrédients de parfum ou d'arôme à composer, lequel procédé mis en œuvre par ordinateur comprend les étapes consistant à : - fournir (105) un ensemble original d'identificateurs numériques de compositions de parfum ou d'arôme d'exemple, lesdits identificateurs numériques de compositions de parfum ou d'arôme d'exemple étant représentatifs de compositions de parfum ou d'arôme matérialisées comprenant au moins deux ingrédients distincts, et - entrainer (110) un dispositif autocodeur ou un dispositif de réseau antagoniste génératif en utilisant l'ensemble original d'identificateurs numériques de compositions de parfum ou d'arôme d'exemple pour générer un modèle génératif de composition de parfum ou d'arôme appris pour générer de nouvelles compositions à base d'ingrédients de parfum ou d'arôme, comprenant au moins deux ingrédients distincts, à composer. Le dispositif autocodeur ou le dispositif de réseau antagoniste génératif entrainé peut être utilisé pour générer de nouvelles compositions à base d'ingrédients de parfum ou d'arôme.
Related patent documents
Latest bibliographic data on file with the International Bureau