EP 3931760 A1 20220105 - TRAINING NEURAL NETWORKS FOR EFFICIENT IMPLEMENTATION ON HARDWARE
Title (en)
TRAINING NEURAL NETWORKS FOR EFFICIENT IMPLEMENTATION ON HARDWARE
Title (de)
TRAINING NEURONALER NETZWERKE FÜR EFFIZIENTES IMPLEMENTIEREN AUF HARDWARE
Title (fr)
APPRENTISSAGE DE RÉSEAUX NEURONAUX POUR UNE MISE EN OEUVRE EFFICACE SUR UN MATÉRIEL
Publication
Application
Priority
- DE 102019202816 A 20190301
- EP 2020054054 W 20200217
Abstract (en)
[origin: WO2020178009A1] A method (100) for training an artificial neural network, ANN (1), which comprises a plurality of neurons (2), comprising the following steps: • a measure of the quality (11) that the ANN (1) has achieved overall within a past time period is determined (110); • one or more neurons (2) are evaluated on the basis of a measure of their respective quantitative contributions (21) to the determined quality (11) (120); • actions (22), by means of which the evaluated neurons (2) are respectively trained in the further course of the training, and/or weights (23) of said neurons (2) in the ANN (1) are defined on the basis of the evaluations (120a) of the neurons (2) (130). The method (200) according to claim 11, wherein a computing unit (4) having hardware resources for a specified number of neurons (2), layers (3a, 3b) of neurons (2) and/or connections (25) between neurons (2) is selected (205a), and wherein a model (1a) of the ANN (1) having a number of neurons (2), layers (3a, 3b) of neurons (2) and/or connections (25) between neurons (2) that exceeds the specified number is selected (205b).
IPC 8 full level
G06N 3/08 (2006.01); G06N 3/04 (2006.01); G06N 3/063 (2006.01)
CPC (source: EP US)
G06N 3/04 (2013.01 - US); G06N 3/063 (2013.01 - EP); G06N 3/082 (2013.01 - EP); G06N 3/047 (2023.01 - EP)
Citation (search report)
See references of WO 2020178009A1
Designated contracting state (EPC)
AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR
Designated extension state (EPC)
BA ME
DOCDB simple family (publication)
DE 102019202816 A1 20200903; CN 113454655 A 20210928; EP 3931760 A1 20220105; US 2022101088 A1 20220331; WO 2020178009 A1 20200910
DOCDB simple family (application)
DE 102019202816 A 20190301; CN 202080017830 A 20200217; EP 2020054054 W 20200217; EP 20705699 A 20200217; US 202017429094 A 20200217