JPWO2021095361A5 - - Google Patents

Download PDF

Info

Publication number
JPWO2021095361A5
JPWO2021095361A5 JP2021555926A JP2021555926A JPWO2021095361A5 JP WO2021095361 A5 JPWO2021095361 A5 JP WO2021095361A5 JP 2021555926 A JP2021555926 A JP 2021555926A JP 2021555926 A JP2021555926 A JP 2021555926A JP WO2021095361 A5 JPWO2021095361 A5 JP WO2021095361A5
Authority
JP
Japan
Prior art keywords
unit
input
data
neural network
layer
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
JP2021555926A
Other languages
English (en)
Japanese (ja)
Other versions
JP7386462B2 (ja
JPWO2021095361A1 (https=
Filing date
Publication date
Application filed filed Critical
Priority claimed from PCT/JP2020/035254 external-priority patent/WO2021095361A1/ja
Publication of JPWO2021095361A1 publication Critical patent/JPWO2021095361A1/ja
Publication of JPWO2021095361A5 publication Critical patent/JPWO2021095361A5/ja
Application granted granted Critical
Publication of JP7386462B2 publication Critical patent/JP7386462B2/ja
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

JP2021555926A 2019-11-11 2020-09-17 演算装置および学習済みモデル Active JP7386462B2 (ja)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
JP2019203988 2019-11-11
JP2019203988 2019-11-11
PCT/JP2020/035254 WO2021095361A1 (ja) 2019-11-11 2020-09-17 演算装置および学習済みモデル

Publications (3)

Publication Number Publication Date
JPWO2021095361A1 JPWO2021095361A1 (https=) 2021-05-20
JPWO2021095361A5 true JPWO2021095361A5 (https=) 2022-07-07
JP7386462B2 JP7386462B2 (ja) 2023-11-27

Family

ID=75912167

Family Applications (1)

Application Number Title Priority Date Filing Date
JP2021555926A Active JP7386462B2 (ja) 2019-11-11 2020-09-17 演算装置および学習済みモデル

Country Status (2)

Country Link
JP (1) JP7386462B2 (https=)
WO (1) WO2021095361A1 (https=)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114648652B (zh) * 2022-03-14 2025-04-11 北京计算机技术及应用研究所 一种利用卷积神经网络和正交变换计算图像哈希值的方法
JP7457752B2 (ja) 2022-06-15 2024-03-28 株式会社安川電機 データ分析システム、データ分析方法、及びプログラム

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110062871B (zh) * 2016-12-09 2024-01-19 通腾全球信息公司 用于基于视频的定位及映射的方法及系统

Similar Documents

Publication Publication Date Title
KR102644947B1 (ko) 뉴럴 네트워크를 위한 트레이닝 방법, 뉴럴 네트워크를 이용한 인식 방법 및 그 장치들
US11922322B2 (en) Exponential modeling with deep learning features
US12393847B2 (en) Gradient adversarial training of neural networks
Chen et al. Ensemble Neural Networks (ENN): A gradient-free stochastic method
KR102492318B1 (ko) 모델 학습 방법 및 장치, 및 데이터 인식 방법
US8694451B2 (en) Neural network system
Lughofer et al. On-line elimination of local redundancies in evolving fuzzy systems
CN112633463B (zh) 用于建模序列数据中长期依赖性的双重递归神经网络架构
Gao et al. A canonical polyadic deep convolutional computation model for big data feature learning in Internet of Things
Wu et al. A multiobjective optimization-based sparse extreme learning machine algorithm
CN109766557A (zh) 一种情感分析方法、装置、存储介质及终端设备
JPWO2021095361A5 (https=)
JP7540632B2 (ja) 半定値計画問題を解く層を有するニューラルネットワーク
US20190325289A1 (en) Optimizing performance of recurrent neural networks
US20200184324A1 (en) Network composition module for a bayesian neuromorphic compiler
Kumar APTx: better activation function than MISH, SWISH, and ReLU's variants used in deep learning
Verma et al. Fuzzy inference network with mamdani fuzzy inference system
WO2022038660A1 (ja) 情報処理装置、情報処理方法、および、情報処理プログラム
Narayanan et al. Introduction to deep learning
CN111868749B (zh) 用于计算条件概率的神经元网络拓扑
KR102704648B1 (ko) 전자 장치 및 그 제어 방법
JP7386462B2 (ja) 演算装置および学習済みモデル
Mustapha et al. Introduction to machine learning and artificial intelligence
KR20210141150A (ko) 이미지 분류 모델을 이용한 이미지 분석 방법 및 장치
Lee Certainty vs. intelligence