EP 3545436 A4 20200506 - ELECTRONIC APPARATUS AND METHOD OF OPERATING THE SAME
Title (en)
ELECTRONIC APPARATUS AND METHOD OF OPERATING THE SAME
Title (de)
ELEKTRONISCHE VORRICHTUNG UND VERFAHREN ZUM BETRIEB DAVON
Title (fr)
APPAREIL ÉLECTRONIQUE ET SON PROCÉDÉ DE FONCTIONNEMENT
Publication
Application
Priority
- KR 20170000789 A 20170103
- KR 20170136612 A 20171020
- KR 2018000069 W 20180103
Abstract (en)
[origin: KR20180080098A] An electronic device comprises: a display unit; a memory to store one or more instructions; and a processor to execute the one or more instructions stored in the memory. The processor executes the one or more instructions to acquire a plurality of images, uses a feature extraction model to extract deep features for the plurality of images, uses the extracted deep features and a classification model to classify the plurality of images into prescribed groups, displays classified results on the display unit, uses the classified results to determine whether the feature extraction model and the classification model need to be updated, and trains at least one among the feature extraction model and the classification model in accordance with a determination result to update the at least one among the feature extraction model and the classification model. The electronic device can estimate deep features of an image by using a rule-based or an artificial intelligence algorithm. If the artificial intelligence algorithm is used to estimate the deep features of the image, the electronic device may use a machine learning, a neural network, or a deep learning algorithm.
IPC 8 full level
G06K 9/00 (2006.01); G06F 16/50 (2019.01); G06F 16/51 (2019.01); G06K 9/46 (2006.01); G06K 9/62 (2006.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01)
CPC (source: EP KR US)
G06F 16/51 (2019.01 - EP US); G06F 16/583 (2019.01 - KR); G06F 18/217 (2023.01 - EP); G06F 18/22 (2023.01 - US); G06F 18/23 (2023.01 - US); G06F 18/24 (2023.01 - US); G06F 18/24143 (2023.01 - EP); G06N 3/045 (2023.01 - EP KR); G06N 3/08 (2013.01 - EP KR); G06V 10/454 (2022.01 - EP US); G06V 10/82 (2022.01 - EP US); G06V 10/94 (2022.01 - US); G06V 20/35 (2022.01 - EP US); G06N 3/02 (2013.01 - US); G06N 3/044 (2023.01 - EP)
Citation (search report)
- [XY] US 2015254532 A1 20150910 - TALATHI SACHIN SUBHASH [US], et al
- [Y] WO 2016077834 A1 20160519 - ZORROA CORP [US]
- [XY] ANONYMOUS: "Convolutional neural network - Wikipedia", 30 December 2016 (2016-12-30), XP055641393, Retrieved from the Internet <URL:https://en.wikipedia.org/w/index.php?title=Convolutional_neural_network&oldid=757325988> [retrieved on 20191112]
- [A] MINGSHENG LONG ET AL: "Learning Transferable Features with Deep Adaptation Networks", 32ND INTERNATIONAL CONFERENCE ON MACHINE LEARNING, 10 February 2015 (2015-02-10), Lille, France, XP055641399
- [A] HOO-CHANG SHIN ET AL: "Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning", IEEE TRANSACTIONS ON MEDICAL IMAGING., vol. 35, no. 5, 11 February 2016 (2016-02-11), US, pages 1285 - 1298, XP055556851, ISSN: 0278-0062, DOI: 10.1109/TMI.2016.2528162
- [X] M. BISHOP CHRISTOPER: "CHAPTER 5: Neural Networks", PATTERN RECOGNITION AND MACHINE LEARNING., 2006, US, pages 225 - 290, XP055679843, ISBN: 978-0-387-31073-2, Retrieved from the Internet <URL:https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf> [retrieved on 20200325]
- See also references of WO 2018128362A1
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
DOCDB simple family (publication)
CN 110168530 A 20190823; CN 110168530 B 20240126; EP 3545436 A1 20191002; EP 3545436 A4 20200506; KR 102428920 B1 20220804; KR 20180080098 A 20180711
DOCDB simple family (application)
CN 201880005869 A 20180103; EP 18735947 A 20180103; KR 20170136612 A 20171020