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检索条件"主题词=Autoencoder"
4258 条 记 录,以下是4181-4190 订阅
Exploring autoencoders for Unsupervised Feature Selection
Exploring Autoencoders for Unsupervised Feature Selection
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International Joint Conference on Neural Networks (IJCNN)
作者: Chandra, B. Sharma, Rajesh K. Indian Inst Technol Delhi Dept Math New Delhi India
Feature selection plays an important role in pattern classification. It is especially an important preprocessing task when there are large number of features in comparison to number of patterns as is the case with gen... 详细信息
来源: 评论
A Deep Learning Approach for Searching Cloud-Hosted Software Projects  15
A Deep Learning Approach for Searching Cloud-Hosted Software...
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15th International Conference on New Trends in Intelligent Software Methodology Tools, and Techniques (SoMeT)
作者: Petrovic, Gajo Dimitrieski, Vladimir Fujita, Hamido Iwate Prefectural Univ Takizawa Iwate Japan Univ Novi Sad Fac Tech Sci Novi Sad Serbia
Modern software development is highly dependent on existing libraries, frameworks and tools. Finding and learning the ones best suited to solve a given problem can sometimes take a considerable amount of time. Search ... 详细信息
来源: 评论
Page Segmentation for Historical Document Images Based on Superpixel Classification with Unsupervised Feature Learning  12
Page Segmentation for Historical Document Images Based on Su...
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12th IAPR International Workshop on Document Analysis Systems (DAS)
作者: Chen, Kai Liu, Cheng-Lin Seuret, Mathias Liwicki, Marcus Hennebert, Jean Ingold, Rolf Univ Fribourg DIVA CH-1700 Fribourg Switzerland Chinese Acad Sci Inst Automat NLPR Beijing 100864 Peoples R China Univ Appl Sci HES SO FR Fribourg Switzerland
In this paper, we present an efficient page segmentation method for historical document images. Many existing methods either rely on hand-crafted features or perform rather slow as they treat the problem as a pixel-le... 详细信息
来源: 评论
Online Marginalized Linear Stacked Denoising autoencoders for Learning from Big Data Stream
Online Marginalized Linear Stacked Denoising Autoencoders fo...
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International Conference on Advanced Computer Science and Information Systems (ICACSIS)
作者: Budiman, Arif Fanany, Mohamad Ivan Basaruddin, Chan Univ Indonesia Fac Comp Sci Depok West Java Indonesia
Big non-stationary data, which comes in gradual fashion or stream, is one important issue in the application of big data to train deep learning machines. In this paper, we focused on a unique variant of traditional au... 详细信息
来源: 评论
EvoAE - A New Evolutionary Method for Training autoencoders for Deep Learning Networks  39
EvoAE - A New Evolutionary Method for Training Autoencoders ...
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39th IEEE Annual International Computer Software and Applications Conference Workshops (COMPSAC)
作者: Lander, Sean Shang, Yi Univ Missouri Dept Comp Sci Columbia MO 65211 USA
Although deep learning has achieved outstanding performances on several difficult machine learning applications, there are multiple issues that make its application on new problems difficult: speed of training, local ... 详细信息
来源: 评论
Unsupervised Deep Hashing for Large-scale Visual Search  6
Unsupervised Deep Hashing for Large-scale Visual Search
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6th International Conference on Image Processing Theory, Tools and Applications (IPTA)
作者: Xia, Zhaoqiang Feng, Xiaoyi Peng, Jinye Hadid, Abdenour Northwestern Polytech Univ Sch Elect & Informat Fremont CA 94539 USA Univ Oulu Ctr Machine Vis Res SF-90100 Oulu Finland
Learning based hashing plays a pivotal role in largescale visual search. However, most existing hashing algorithms tend to learn shallow models that do not seek representative binary codes. In this paper, we propose a... 详细信息
来源: 评论
Cartesian Abstraction Can Yield 'Cognitive Maps'  7th
Cartesian Abstraction Can Yield 'Cognitive Maps'
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7th Annual International Conference on Biologically Inspired Cognitive Architectures (BICA)
作者: Lorincz, Andras Eotvos Lorand Univ Budapest Hungary
It has been long debated how the so called cognitive map, the set of place cells, develops in rat hippocampus. The function of this organ is of high relevance, since the hippocampus is the key component of the medial ... 详细信息
来源: 评论
A Deep Neural Network Architecture Using Dimensionality Reduction with Sparse Matrices  1
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23rd International Conference on Neural Information Processing (ICONIP)
作者: Matsumoto, Wataru Hagiwara, Manabu Boufounos, Petros T. Fukushima, Kunihiko Mariyama, Toshisada Zhao Xiongxin Mitsubishi Electr Corp Informat Technol R&D Ctr Kamakura Kanagawa Japan Chiba Univ Chiba Japan Mitsubishi Elect Res Labs Cambridge MA USA Fuzzy Logic Syst Inst Fukuoka Japan
We present a new deep neural network architecture, motivated by sparse random matrix theory that uses a low-complexity embedding through a sparse matrix instead of a conventional stacked autoencoder. We regard autoenc... 详细信息
来源: 评论
ALZHEIMER'S DISEASE DIAGNOSTICS BY ADAPTATION OF 3D CONVOLUTIONAL NETWORK  23
ALZHEIMER'S DISEASE DIAGNOSTICS BY ADAPTATION OF 3D CONVOLUT...
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23rd IEEE International Conference on Image Processing (ICIP)
作者: Hosseini-Asl, Ehsan Keynton, Robert El-Baz, Ayman Univ Louisville Elect & Comp Engn Dept Louisville KY 40292 USA Univ Louisville Dept Bioengn Louisville KY 40292 USA
Early diagnosis, playing an important role in preventing progress and treating the Alzheimer's disease (AD), is based on classification of features extracted from brain images. The features have to accurately capt... 详细信息
来源: 评论
A Map-reduce Method for Training autoencoders on Xeon Phi  15
A Map-reduce Method for Training Autoencoders on Xeon Phi
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IEEE International Conference on Computer and Information
作者: Yao, Qiongjie Liao, Xiaofei Jin, Hai Huazhong Univ Sci & Technol Sch Comp Sci & Technol Cluster & Grid Comp Lab Serv Comp Technol & Syst Lab Wuhan 430074 Peoples R China
The stacked autoencoder is a deep learning model that consists of multiple autoencoders. This model has been widely applied in numerous machine learning applications. A significant amount of effort has been made to in... 详细信息
来源: 评论