COARSE-TO-FINE CONVOLUTIONAL NEURAL NETWORK-BASED MULTILABEL CLASS CLASSIFICATION METHOD AND APPARATUS
The present invention relates to a coarse-to-fine convolutional neural network-based multilabel class classification apparatus that generates a hierarchical structure-based plurality of group labels for a plurality of classes to be classified, by using a disjoint grouping method, predicts a class be...
Saved in:
Main Authors | , , , |
---|---|
Format | Patent |
Language | English French Korean |
Published |
11.05.2023
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | The present invention relates to a coarse-to-fine convolutional neural network-based multilabel class classification apparatus that generates a hierarchical structure-based plurality of group labels for a plurality of classes to be classified, by using a disjoint grouping method, predicts a class belonging to each of the plurality of group labels from among the plurality of classes by using a coarse-to-fine convolutional neural network including a main network and one or more sub-networks, completes training the coarse-to-fine convolutional neural network through prediction, and when an image including an object corresponding to a class is input, classifies the class included in the image as the main network of the coarse-to-fine convolutional neural network that has been trained receives an input of a feature map input from a last convolutional layer of the one or more sub-networks.
La présente invention concerne un appareil de classification de classes à plusieurs étiquettes basés sur un réseau neuronal convolutif grossier à fin qui génère une pluralité d'étiquettes de groupe basée sur une structure hiérarchique pour une pluralité de classes à classifier, en utilisant un procédé de regroupement disjoint, prédit une classe appartenant à chacune de la pluralité d'étiquettes de groupe parmi la pluralité de classes en utilisant un réseau neuronal convolutif grossier à fin comprenant un réseau principal et un ou plusieurs sous-réseaux, achève l'entraînement du réseau neuronal convolutif grossier à fin par prédiction, et lorsqu'une image comprenant un objet correspondant à une classe est entrée, classifie la classe incluse dans l'image à mesure que le réseau principal du réseau neuronal convolutif grossier à fin qui a été entraîné reçoit une entrée d'une entrée de carte de caractéristiques à partir d'une dernière couche de convolution du ou des sous-réseaux.
본 발명은 코스-투-파인 컨볼루션 뉴럴 네트워크(Coarse-to-Fine Convolutional Neural Network) 기반 다중 레이블 클래스 분류 장치로서, 디스조인트(disjoint) 그룹화 방법을 이용하여 분류 대상이 되는 복수의 클래스에 대한 계층적 구조 기반의 복수의 그룹 레이블을 생성하고, 메인 네트워크 및 하나 이상의 서브 네트워크를 포함하는 코스-투-파인 컨볼루션 뉴럴 네트워크를 이용하여 복수의 클래스 중 복수의 그룹 레이블 각각에 속하는 클래스를 예측하고, 예측을 통해 코스-투-파인 컨볼루션 뉴럴 네트워크의 학습을 완료하고, 클래스에 상응하는 객체를 포함하는 이미지가 입력되는 경우, 학습이 완료된 코스-투-파인 컨볼루션 뉴럴 네트워크의 메인 네트워크가 하나 이상의 서브 네트워크의 마지막 컨볼루션 레이어에서 입력되는 특징 맵을 입력 받아, 이미지에 포함되는 클래스를 분류하도록 한다. |
---|---|
AbstractList | The present invention relates to a coarse-to-fine convolutional neural network-based multilabel class classification apparatus that generates a hierarchical structure-based plurality of group labels for a plurality of classes to be classified, by using a disjoint grouping method, predicts a class belonging to each of the plurality of group labels from among the plurality of classes by using a coarse-to-fine convolutional neural network including a main network and one or more sub-networks, completes training the coarse-to-fine convolutional neural network through prediction, and when an image including an object corresponding to a class is input, classifies the class included in the image as the main network of the coarse-to-fine convolutional neural network that has been trained receives an input of a feature map input from a last convolutional layer of the one or more sub-networks.
La présente invention concerne un appareil de classification de classes à plusieurs étiquettes basés sur un réseau neuronal convolutif grossier à fin qui génère une pluralité d'étiquettes de groupe basée sur une structure hiérarchique pour une pluralité de classes à classifier, en utilisant un procédé de regroupement disjoint, prédit une classe appartenant à chacune de la pluralité d'étiquettes de groupe parmi la pluralité de classes en utilisant un réseau neuronal convolutif grossier à fin comprenant un réseau principal et un ou plusieurs sous-réseaux, achève l'entraînement du réseau neuronal convolutif grossier à fin par prédiction, et lorsqu'une image comprenant un objet correspondant à une classe est entrée, classifie la classe incluse dans l'image à mesure que le réseau principal du réseau neuronal convolutif grossier à fin qui a été entraîné reçoit une entrée d'une entrée de carte de caractéristiques à partir d'une dernière couche de convolution du ou des sous-réseaux.
본 발명은 코스-투-파인 컨볼루션 뉴럴 네트워크(Coarse-to-Fine Convolutional Neural Network) 기반 다중 레이블 클래스 분류 장치로서, 디스조인트(disjoint) 그룹화 방법을 이용하여 분류 대상이 되는 복수의 클래스에 대한 계층적 구조 기반의 복수의 그룹 레이블을 생성하고, 메인 네트워크 및 하나 이상의 서브 네트워크를 포함하는 코스-투-파인 컨볼루션 뉴럴 네트워크를 이용하여 복수의 클래스 중 복수의 그룹 레이블 각각에 속하는 클래스를 예측하고, 예측을 통해 코스-투-파인 컨볼루션 뉴럴 네트워크의 학습을 완료하고, 클래스에 상응하는 객체를 포함하는 이미지가 입력되는 경우, 학습이 완료된 코스-투-파인 컨볼루션 뉴럴 네트워크의 메인 네트워크가 하나 이상의 서브 네트워크의 마지막 컨볼루션 레이어에서 입력되는 특징 맵을 입력 받아, 이미지에 포함되는 클래스를 분류하도록 한다. |
Author | PAIK, Joon Ki PARK, Jin Ho KIM, Hee Gwang SHIN, Min Woo |
Author_xml | – fullname: SHIN, Min Woo – fullname: PARK, Jin Ho – fullname: PAIK, Joon Ki – fullname: KIM, Hee Gwang |
BookMark | eNqNizkKwzAQRVUkRbY7CFILvDRpx_IYi8iaoCUujQlyFWyDc3-yHiDF-6_5b8tW4zTGDRskgXUoPIlKGeSSzJV08IoMaG4w2I98S_YsCnBY8iZorzQUqLnU4Nx3VaUkvDPeoK-p5GBeXC5gwQe3Z-uhvy_x8POOHSv0shZxnrq4zP0tjvHRtZQlWZ6ckjxLIc3_ez0BGyo3_Q |
ContentType | Patent |
DBID | EVB |
DatabaseName | esp@cenet |
DatabaseTitleList | |
Database_xml | – sequence: 1 dbid: EVB name: esp@cenet url: http://worldwide.espacenet.com/singleLineSearch?locale=en_EP sourceTypes: Open Access Repository |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Medicine Chemistry Sciences Physics |
DocumentTitleAlternate | PROCÉDÉ ET APPAREIL DE CLASSIFICATION DE CLASSES À PLUSIEURS ÉTIQUETTES BASÉS SUR UN RÉSEAU NEURONAL CONVOLUTIF GROSSIER À FIN 코스-투-파인 컨볼루션 뉴럴 네트워크 기반 다중 레이블 클래스 분류 방법 및 장치 |
ExternalDocumentID | WO2023080321A1 |
GroupedDBID | EVB |
ID | FETCH-epo_espacenet_WO2023080321A13 |
IEDL.DBID | EVB |
IngestDate | Fri Oct 04 05:00:38 EDT 2024 |
IsOpenAccess | true |
IsPeerReviewed | false |
IsScholarly | false |
Language | English French Korean |
LinkModel | DirectLink |
MergedId | FETCHMERGED-epo_espacenet_WO2023080321A13 |
Notes | Application Number: WO2021KR17922 |
OpenAccessLink | https://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230511&DB=EPODOC&CC=WO&NR=2023080321A1 |
ParticipantIDs | epo_espacenet_WO2023080321A1 |
PublicationCentury | 2000 |
PublicationDate | 20230511 |
PublicationDateYYYYMMDD | 2023-05-11 |
PublicationDate_xml | – month: 05 year: 2023 text: 20230511 day: 11 |
PublicationDecade | 2020 |
PublicationYear | 2023 |
RelatedCompanies | CHUNG ANG UNIVERSITY INDUSTRY ACADEMIC COOPERATION FOUNDATION |
RelatedCompanies_xml | – name: CHUNG ANG UNIVERSITY INDUSTRY ACADEMIC COOPERATION FOUNDATION |
Score | 3.4458797 |
Snippet | The present invention relates to a coarse-to-fine convolutional neural network-based multilabel class classification apparatus that generates a hierarchical... |
SourceID | epo |
SourceType | Open Access Repository |
SubjectTerms | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING PHYSICS |
Title | COARSE-TO-FINE CONVOLUTIONAL NEURAL NETWORK-BASED MULTILABEL CLASS CLASSIFICATION METHOD AND APPARATUS |
URI | https://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230511&DB=EPODOC&locale=&CC=WO&NR=2023080321A1 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3da8IwEA_iPt82t7EPNwobfQvrp7UPMtI0RbfalH6ob2JrCmNDZXbs318a6-aTD0ngDkJycLn7JXcXAJ7mRl7ommJCi4NlaGjKDHZ1I4eskxvMVrV5NhcBskGnnxqvE3PSAJ_bXBhRJ_RHFEfkGpVzfS_Feb36v8RyRWzl-jl756Tli5f0XLlGx9yf5g6E7Do9ElKXYhljjtvkINrwuoquqYhjpYPKka4q7ZORU-WlrHaNincGDkM-36I8B42PZQuc4O3fay1wPKyfvFvgSMRo5mtOrPVwfQEKTFEUE5hQ6A0CImEajKifbgrbSgFJIzEkYxq9QQfFxJWGqZ8MfOQQX8I-iuNNP_DqTGJpSJI-dSUU8BaGKEJJGl-CR48kuA_50qd_kpqO6e4-9SvQXCwX7BpIijmzbItZJlMLwzRZZqszDpR0ndl5wUz7BrT3zXS7n30HTrUKhlaZ3kobNMuvb3bPbXWZPQgR_wJcf451 |
link.rule.ids | 230,309,786,891,25594,76904 |
linkProvider | European Patent Office |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1bS8MwFA7D23zTqXiZWlD6Fux1XR-G9JLSurYpbbrtbaxdCqJsw1X8-6Zdp3vaQxI4B0ISOEm-nHO-APA8V_JClgQVagwsQ0USZrAvKzmkvVyhuijNs3kdIBv23FR5m6iTFvjc5sLUPKE_NTkis6ic2XtZ79er_0csu46tXL9k70y0fHXIwOYbdMzu0-wCwdvmAEXYxhZvWQy38WG80fUFWRINhpUONQYKK6Z9NDKrvJTV7qHinIGjiPW3KM9B62PZAW1r-_daB5wEjcu7A47rGM18zYSNHa4vQGFhI04QJBg6Xog4C4cj7KcbYlsuRGlcN2SM4yE0jQTZXJD6xPMNE_mc5RtJsqk9p8kk5gJEXGxzRshKFBmxQdLkEjw5iFguZEOf_q3UdIx35ylfgYPFckGvASeoM03XqKZSsVBUlWa6OGNASZapnhdU1W9Ad19Pt_vVj6DtksCf-l44vAOnlapysItiFxyUX9_0np3bZfZQL_cvLaiRZg |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Apatent&rft.title=COARSE-TO-FINE+CONVOLUTIONAL+NEURAL+NETWORK-BASED+MULTILABEL+CLASS+CLASSIFICATION+METHOD+AND+APPARATUS&rft.inventor=SHIN%2C+Min+Woo&rft.inventor=PARK%2C+Jin+Ho&rft.inventor=PAIK%2C+Joon+Ki&rft.inventor=KIM%2C+Hee+Gwang&rft.date=2023-05-11&rft.externalDBID=A1&rft.externalDocID=WO2023080321A1 |