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检索条件"主题词=Denoising Autoencoder"
346 条 记 录,以下是301-310 订阅
Predicting Unmeasured Region of the Efficiency Map of a Speed Reducer Using a denoising Auto-encoder  3
Predicting Unmeasured Region of the Efficiency Map of a Spee...
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3rd International Conference on Computational Intelligence and Applications (ICCIA)
作者: Shin, Crino Jin, Yongsik Jeong, Seunghyun Yun, Jongpil Korea Inst Ind Technol KITECH Cheonan South Korea Kyungpook Natl Univ Daegu South Korea Kyungpook Natl Univ Dept Elect Engn Daegu South Korea
This paper presents a Remaining Useful Life (RUL) prediction method for a speed reducer based on denoising auto-encoder (DAE). Constructing the efficiency map of the reducer is an important process for predicting the ... 详细信息
来源: 评论
MULTI-TASK autoencoder FOR NOISE-ROBUST SPEECH RECOGNITION
MULTI-TASK AUTOENCODER FOR NOISE-ROBUST SPEECH RECOGNITION
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IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
作者: Zhang, Haoyi Liu, Conggui Inoue, Nakamasa Shinoda, Koichi Tokyo Inst Technol Tokyo Japan
For speech recognition in noisy environments, we propose a multi-task autoencoder which estimates not only clean speech features but also noise features from noisy speech. We introduce the deSpeeching autoencoder, whi... 详细信息
来源: 评论
OPEN SET RECOGNITION BY REGULARISING CLASSIFIER WITH FAKE DATA GENERATED BY GENERATIVE ADVERSARIAL NETWORKS
OPEN SET RECOGNITION BY REGULARISING CLASSIFIER WITH FAKE DA...
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IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
作者: Jo, Inhyuk Kim, Jungtaek Kang, Hyohyeong Kim, Yong-Deok Choi, Seungjin POSTECH Dept Comp Sci & Engn Pohang South Korea Samsung Elect Software R&D Ctr Device Solut Seoul South Korea
We present a new method to generate fake data in unknown classes in generative adversarial networks (GANs) framework. The generator in GANs is trained to generate somewhat similar to data in known classes but the diff... 详细信息
来源: 评论
Supervised deep learning embeddings for the prediction of cervical cancer diagnosis
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PEERJ COMPUTER SCIENCE 2018年 第5期4卷 e154页
作者: Fernandes, Kelwin Chicco, Davide Cardoso, Jaime S. Fernandes, Jessica INESC TEC Inst Engn Sistemas & Comp Tecnol & Ciencia Porto Portugal Univ Porto Porto Portugal Princess Margaret Canc Ctr Toronto ON Canada Univ Cent Venezuela Caracas Venezuela
Cervical cancer remains a significant cause of mortality all around the world, even if it can be prevented and cured by removing affected tissues in early stages. Providing universal and efficient access to cervical s... 详细信息
来源: 评论
Unsupervised Sequential Outlier Detection With Deep Architectures
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IEEE TRANSACTIONS ON IMAGE PROCESSING 2017年 第9期26卷 4321-4330页
作者: Lu, Weining Cheng, Yu Xiao, Cao Chang, Shiyu Huang, Shuai Liang, Bin Huang, Thomas Tsinghua Univ Dept Automat Beijing 100084 Peoples R China IBM TJ Watson Res Ctr Yorktown Hts NY 10562 USA Univ Washington Dept Ind & Syst Engn Seattle WA 98105 USA Univ Illinois Beckman Inst Urbana IL 61801 USA
Unsupervised outlier detection is a vital task and has high impact on a wide variety of applications domains, such as image analysis and video surveillance. It also gains longstanding attentions and has been extensive... 详细信息
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Application of stack marginalised sparse denoising auto-encoder in fault diagnosis of rolling bearing
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JOURNAL OF ENGINEERING-JOE 2018年 第16期2018卷 1772-1777页
作者: Zhang, Junling Chen, Zhigang Du, Xiaolei Xu, Xu Yu, Miao Beijing Univ Civil Engn & Architecture Inst Elect & Mech & Vehicle Engn Beijing 100044 Peoples R China Construct Safety Monitoring Engn Technol Res Ctr Beijing 100037 Peoples R China
When a fracturing vehicle is working, it generally needs to bear high loads, media corrosion and erosion. For this special working environment, this study proposes a rolling bearing fault diagnosis method based on sta... 详细信息
来源: 评论
Biomedical ontology alignment: an approach based on representation learning
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JOURNAL OF BIOMEDICAL SEMANTICS 2018年 第1期9卷 21页
作者: Kolyvakis, Prodromos Kalousis, Alexandros Smith, Barry Kiritsis, Dimitris Ecole Polytech Fed Lausanne Route Cantonale CH-1015 Lausanne Switzerland Univ Appl Sci HES SO Western Switzerland Carouge Business Informat Dept Lausanne Switzerland SUNY Buffalo Dept Philosophy 104 Pk Hall Buffalo NY 14260 USA SUNY Buffalo Dept Biomed Informat 104 Pk Hall Buffalo NY 14260 USA
Background: While representation learning techniques have shown great promise in application to a number of different NLP tasks, they have had little impact on the problem of ontology matching. Unlike past work that h... 详细信息
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ROBUST RECOGNITION OF SPEECH WITH BACKGROUND MUSIC IN ACOUSTICALLY UNDER-RESOURCED SCENARIOS
ROBUST RECOGNITION OF SPEECH WITH BACKGROUND MUSIC IN ACOUST...
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IEEE International Conference on Acoustics, Speech and Signal Processing
作者: Jiri Malek Jindrich Zdansky Petr Cerva Faculty of Mechatronics Informatics and Interdisciplinary Studies Technical University of Liberec Studentská 2 461 17 Liberec Czech Republic
This paper addresses the task of Automatic Speech Recognition (ASR) with music in the background. We consider two different situations: 1) scenarios with very small amount of labeled training utterances (duration 1 ho... 详细信息
来源: 评论
Open Set Recognition by Regularising Classifier with Fake Data Generated by Generative Adversarial Networks
Open Set Recognition by Regularising Classifier with Fake Da...
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IEEE International Conference on Acoustics, Speech and Signal Processing
作者: Inhyuk Jo Jungtaek Kim Hyohyeong Kang Yong-Deok Kim Seungjin Choi Department of Computer Science and Engineering POSTECH Korea Software R&D Center Device Solutions Samsung Electronics Korea
We present a new method to generate fake data in unknown classes in generative adversarial networks (GANs) framework. The generator in GANs is trained to generate somewhat similar to data in known classes but the diff... 详细信息
来源: 评论
Medical image denoising using convolutional denoising autoencoders  16
Medical image denoising using convolutional denoising autoen...
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16th IEEE International Conference on Data Mining (ICDM)
作者: Gondara, Lovedeep Simon Fraser Univ Dept Comp Sci Burnaby BC Canada
Image denoising is an important pre-processing step in medical image analysis. Different algorithms have been proposed in past three decades with varying denoising performances. More recently, having outperformed all ... 详细信息
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