堀 智之
著者に関連した記事は2件です。
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第15回
手元画像解析と機械学習に基づく妨害破壊行為検知手法の開発
著者:
出町 和之,陳 実,堀 智之,（東京大）
発刊日:
公開日:
キーワードタグ:
Convolutional Neural Network Deep Neural Network Hand Behavior Identification Insider Sabotage Long Short Term Memory Nuclear Security Time-Series Data Analysis
出町 和之,陳 実,堀 智之,（東京大）
発刊日:
公開日:
キーワードタグ:
Convolutional Neural Network Deep Neural Network Hand Behavior Identification Insider Sabotage Long Short Term Memory Nuclear Security Time-Series Data Analysis
In this research, a new method was developed to identify the “hand behavior” of malicious sabotage behaviors. The Convolutional Neural Network (CNN) and the Long Short Term Memory (LSTM) were applied for analysis of the time-series data of hand behavior images and identification of hand behavior....
英字タイトル:
Development of Sabotage Behavior Detection by Hand Image Analysis and Machine Learning
英字タイトル:
Development of Sabotage Behavior Detection by Hand Image Analysis and Machine Learning
第16回
深層学習を用いたＥＣＴ信号からのキズ深さ同定
著者:
出町 和之,堀 智之,（東京大）
発刊日:
公開日:
キーワードタグ:
Convolutional Neural Network Deep Learning Eddy Current Testing Lift-off Fluctuation
出町 和之,堀 智之,（東京大）
発刊日:
公開日:
キーワードタグ:
Convolutional Neural Network Deep Learning Eddy Current Testing Lift-off Fluctuation
A deep learning model has been proposed to estimate flaw depth from ECT signals. The applicability of deep learning to data mixed with unknown parameters for defects was verified. The applicability of deep learning to data assuming lift-off fluctuation during measurement was verified....
英字タイトル:
Flaw Depth Identification from ECT Signal Using Deep Learning
英字タイトル:
Flaw Depth Identification from ECT Signal Using Deep Learning