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检索条件"主题词=Autoencoder"
4298 条 记 录,以下是3901-3910 订阅
排序:
Homogenization of Breast MRI across Imaging Centers and Feature Analysis using Unsupervised Deep Embedding
Homogenization of Breast MRI across Imaging Centers and Feat...
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Conference on Medical Imaging - Computer-Aided Diagnosis
作者: Samala, Ravi K. Chan, Heang-Ping Hadjiiski, Lubomir Paramagul, Chintana Helvie, Mark A. Neal, Colleen H. Univ Michigan Dept Radiol Ann Arbor MI 48109 USA
We propose an intensity-based technique to homogenize dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data acquired at six institutions. A total of 234 T1-weighted MRI volumes acquired at the peak kinet... 详细信息
来源: 评论
Interference Detection and Recognition Based on Signal Reconstruction Using Recurrent Neural Network
Interference Detection and Recognition Based on Signal Recon...
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IEEE Global Communications Conference (IEEE GLOBECOM)
作者: Wu, Qianqian Sun, Zhuo Zhou, Xue Beijing Univ Posts & Telecommun Wireless Signal Proc & Network Lab Beijing 100876 Peoples R China
Interference detection using deep neural network has recently received increasing attention due to its capability in learning rich features of data. In this paper, we proposed a low-complexity blind interference detec... 详细信息
来源: 评论
A LEARNING APPROACH TO WIRELESS INFORMATION AND POWER TRANSFER SIGNAL AND SYSTEM DESIGN  44
A LEARNING APPROACH TO WIRELESS INFORMATION AND POWER TRANSF...
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44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
作者: Varasteh, Morteza Piovano, Enrico Clerckx, Bruno Imperial Coll London Dept Elect & Elect Engn London England
The end-to-end learning of Simultaneous Wireless Information and Power Transfer (SWIPT) over a noisy channel is studied. Adopting a nonlinear model for the Energy Harvester (EH) at the receiver, a joint optimization o... 详细信息
来源: 评论
EE-AE: AN EXCLUSIVITY ENHANCED UNSUPERVISED FEATURE LEARNING APPROACH  44
EE-AE: AN EXCLUSIVITY ENHANCED UNSUPERVISED FEATURE LEARNING...
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44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
作者: Guo, Jingcai Guo, Song Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China
Unsupervised learning is becoming more and more important recently. As one of its key components, the autoencoder (AE) aims to learn a latent feature representation of data which is more robust and discriminative. How... 详细信息
来源: 评论
Rethinking Planar Homography Estimation Using Perspective Fields  14th
Rethinking Planar Homography Estimation Using Perspective Fi...
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14th Asian Conference on Computer Vision (ACCV)
作者: Zeng, Rui Denman, Simon Sridharan, Sridha Fookes, Clinton Queensland Univ Technol Brisbane Qld Australia
Planar homography estimation refers to the problem of computing a bijective linear mapping of pixels between two images. While this problem has been studied with convolutional neural networks (CNNs), existing methods ... 详细信息
来源: 评论
Combining feature selection, feature learning and ensemble learning for software fault prediction  11
Combining feature selection, feature learning and ensemble l...
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11th International Conference on Knowledge and Systems Engineering (KSE)
作者: Hung Duy Tran Le Thi My Hanh Nguyen Thanh Binh Univ Danang Dept Informat Technol Univ Sci & Technol Danang Vietnam
This paper studies a combination of feature selection and ensemble learning to address the feature redundancy and class imbalance problems in software fault prediction. Also, a deep learning model is used to generate ... 详细信息
来源: 评论
Structural Role Enhanced Attributed Network Embedding  20th
Structural Role Enhanced Attributed Network Embedding
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20th International Conference on Web Information Systems Engineering (WISE)
作者: Li, Zhao Wang, Xin Li, Jianxin Zhang, Qingpeng Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China Tianjin Key Lab Cognit Comp & Applicat Tianjin Peoples R China Deakin Univ Sch Informat Technol Melbourne Vic Australia City Univ Hong Kong Sch Data Sci Hong Kong Peoples R China
In recent years, network embedding methods based on deep learning to process network structure data have attracted widespread attention. It aims to represent nodes in the network as low-dimensional dense real-value ve... 详细信息
来源: 评论
A Comparison of CasPer Against Other ML Techniques for Stress Recognition  26th
A Comparison of CasPer Against Other ML Techniques for Stres...
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26th International Conference on Neural Information Processing (ICONIP) of the Asia-Pacific-Neural-Network-Society (APNNS)
作者: Sekoranja, Jack Michael Harding Australian Natl Univ Canberra ACT Australia
When developing multi-layer neural networks (MLNNs), determining an appropriate size can be computationally intensive. Cascade Correlation algorithms such as CasPer attempt to address this, however, associated researc... 详细信息
来源: 评论
Dimensionality Reduction for Clustering and Cluster Tracking of Cytometry Data  28th
Dimensionality Reduction for Clustering and Cluster Tracking...
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28th International Conference on Artificial Neural Networks (ICANN)
作者: Putri, Givanna H. Read, Mark N. Koprinska, Irena Ashhurst, Thomas M. King, Nicholas J. C. Univ Sydney Sch Comp Sci Sydney NSW 2006 Australia Univ Sydney Ctr Excellence Adv Food Engin Sydney NSW 2006 Australia Univ Sydney Sch Chem & Biomol Engn Sydney NSW 2006 Australia Univ Sydney Charles Perkins Ctr Sydney NSW 2006 Australia Univ Sydney Sydney Cytometry Facil Sydney NSW 2006 Australia Univ Sydney Discipline Pathol Sydney NSW 2006 Australia
Mass cytometry is a new high-throughput technology that is becoming a cornerstone in immunology and cell biology research. With technological advancement, the number of cellular characteristics cytometry can simultane... 详细信息
来源: 评论
Exploiting Tri-types of Information for Attributed Network Embedding  12th
Exploiting Tri-types of Information for Attributed Network E...
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12th International Conference on Knowledge Science, Engineering and Management (KSEM)
作者: Zhang, Cheng Zhang, Le Guo, Xiaobo Qi, Ying Univ Chinese Acad Sci Sch Cyber Secur Beijing Peoples R China Chinese Acad Sci State Key Lab Informat Secur Beijing Peoples R China Chinese Acad Sci Inst Informat Engn Beijing Peoples R China
With a surge of network data, attributed networks are widely applied for various applications. Recently, how to embed an attributed network into a low-dimensional representation space has gained a lot of attention. No... 详细信息
来源: 评论