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检索条件"主题词=Autoencoder"
4298 条 记 录,以下是3831-3840 订阅
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IL4IoT: Incremental Learning for Internet-of-Things Devices  1
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15th European Conference on Ambient Intelligence (AmI)
作者: Bao, Yuanyuan Chen, Wai China Mobile Res Inst Beijing Peoples R China
Considering that Internet-of-Things (IoT) devices are often deployed in highly dynamic environments, mainly due to their continuous exposure to end-users' living environments, it is imperative that the devices can... 详细信息
来源: 评论
autoencoders and recommender systems: COFILS approach
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EXPERT SYSTEMS WITH APPLICATIONS 2017年 89卷 81-90页
作者: Barbieri, Julio Alvim, Leandro G. M. Braida, Filipe Zimbrao, Geraldo Univ Fed Rio de Janeiro PESC COPPE CT Cidade UnivPOB 68511 Rio De Janeiro Brazil Univ Fed Rio de Janeiro DCC IM BR-26020740 Rio De Janeiro Brazil
Collaborative Filtering to Supervised Learning (COFILS) transforms a Collaborative Filtering (CF) problem into classical Supervised Learning (SL) problem. Applying COFILS reduces data sparsity and makes it possible to... 详细信息
来源: 评论
Machine Learning for Feature Selection and Cluster Analysis in Drug Utilisation Research
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CURRENT EPIDEMIOLOGY REPORTS 2019年 第3期6卷 364-372页
作者: Khalid, Sara Prieto-Alhambra, Daniel Nuffield Dept Orthopaed Rheumatol Musculoskeletal Old Rd Oxford OX3 7LD England
Purpose of ReviewMachine learning methods are increasingly used in health data mining. We describe current unsupervised learning methods for phenotyping and discovery and illustrate their application for detecting fea... 详细信息
来源: 评论
IMPROVING EMOTION CLASSIFICATION THROUGH VARIATIONAL INFERENCE OF LATENT VARIABLES  44
IMPROVING EMOTION CLASSIFICATION THROUGH VARIATIONAL INFEREN...
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44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
作者: Parthasarathy, Srinivas Rozgic, Viktor Sun, Ming Wang, Chao Univ Texas Dallas Richardson TX 75083 USA
Conventional models for emotion recognition from speech signal are trained in supervised fashion using speech utterances with emotion labels. In this study we hypothesize that speech signal depends on multiple latent ... 详细信息
来源: 评论
AMS-SFE: TOWARDS AN ALIGNMENT OF MANIFOLD STRUCTURES VIA SEMANTIC FEATURE EXPANSION FOR ZERO-SHOT LEARNING
AMS-SFE: TOWARDS AN ALIGNMENT OF MANIFOLD STRUCTURES VIA SEM...
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IEEE International Conference on Multimedia and Expo (ICME)
作者: Guo, Jingcai Guo, Song Hong Kong Polytech Univ Dept Comp Kowloon Hong Kong Peoples R China
Zero-shot learning (ZSL) aims at recognizing unseen classes with knowledge transferred from seen classes. This is typically achieved by exploiting a semantic feature space (FS) shared by both seen and unseen classes, ... 详细信息
来源: 评论
User Embeddings Based on Mobile App Behavior Data  17th
User Embeddings Based on Mobile App Behavior Data
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17th International Conference on Smart Living and Public Health (ICOST)
作者: Singla, Kushal Abrol, Satyen Park, Sungdeuk Samsung R&D Inst Bangalore Karnataka India Samsung Elect Suwon South Korea
We consider a smart phone scenario with a number of apps used by a user. The app usage data provides information about the user behavior, which can be used to identify the user demographics and interest and in turn is... 详细信息
来源: 评论
Detecting process instabilities in industrial gas metal arc welding time series
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Procedia Manufacturing 2020年 52卷 150-155页
作者: Vanessa Kirchner Ivan Vishev Mario Rossdeutscher Mercedes-Benz AG Mercedesstraβe 120 70546 Stuttgart Germany Eberhard Karls Universität Tübingen Geschwister-Scholl-Platz 72074 Tübingen Germany
Gas metal arc welding is widely used in industrial series production for joining aluminum. A lot of factors, such as instabilities and complex dependencies, influence the quality of the resulting welding seams. It is ... 详细信息
来源: 评论
Smile Detection Using Data Amalgamation
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Procedia Computer Science 2020年 167卷 979-986页
作者: Irshaad Ali Mohit Dua Department Of Computer Engineering NIT Kutukshetra Kurukshetra 136119 India
A smile is a specific movement of face muscles to relay an optimistic feeling. A smile represents satisfaction and happiness. Many application created using smile detection technology, for example product rating, pati... 详细信息
来源: 评论
An efficient deep learning model for intrusion classification and prediction in 5G and IoT networks  53
An efficient deep learning model for intrusion classificatio...
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53rd Annual Conference on Information Sciences and Systems (CISS)
作者: Rezvy, Shahadate Luo, Yuan Petridis, Miltos Lasebae, Aboubaker Zebin, Tahmina Middlesex Univ London Sch Sci & Technol London England Univ Westminster Sch Comp Sci & Engn London England
A Network Intrusion Detection System is a critical component of every internet-connected system due to likely attacks from both external and internal sources. Such Security systems are used to detect network born atta... 详细信息
来源: 评论
Named Entity Recognition with Homophones-Noisy Data  16th
Named Entity Recognition with Homophones-Noisy Data
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16th Pacific Rim International Conference on Artificial Intelligence (PRICAI)
作者: Liu, Zhicheng Wu, Gang Shanghai Jiao Tong Univ Shanghai Peoples R China
General named entity recognition systems exclusively focus on higher accuracy regardless of dirty data. However, raw source data face serious challenges specially that are originated from automated speech recognition ... 详细信息
来源: 评论