Deep Learning: Concepts and Architectures - Studies in Computational Intelligence
Latest Publications

TOTAL DOCUMENTS

(FIVE YEARS 11)

H-INDEX

(FIVE YEARS 1)

Published By Springer International Publishing

9783030317553, 9783030317560

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Constructing a Convolutional Neural Network with a Suitable Capacity for a Semantic Segmentation Task

Deep Learning: Concepts and Architectures - Studies in Computational Intelligence ◽

10.1007/978-3-030-31756-0_8 ◽

2019 ◽

pp. 237-268

Author(s):

Yalong Jiang ◽

Zheru Chi

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

Semantic Segmentation ◽

Segmentation Task

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Heterogeneous Computing System for Deep Learning

Deep Learning: Concepts and Architectures - Studies in Computational Intelligence ◽

10.1007/978-3-030-31756-0_10 ◽

2019 ◽

pp. 287-319

Author(s):

Mihaela Maliţa ◽

George Vlǎduţ Popescu ◽

Gheorghe M. Ştefan

Keyword(s):

Deep Learning ◽

Heterogeneous Computing ◽

Computing System ◽

Heterogeneous Computing System

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Deep Learning for Learning Graph Representations

Deep Learning: Concepts and Architectures - Studies in Computational Intelligence ◽

10.1007/978-3-030-31756-0_6 ◽

2019 ◽

pp. 169-210

Author(s):

Wenwu Zhu ◽

Xin Wang ◽

Peng Cui

Keyword(s):

Deep Learning ◽

Graph Representations

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The Encoder-Decoder Framework and Its Applications

Deep Learning: Concepts and Architectures - Studies in Computational Intelligence ◽

10.1007/978-3-030-31756-0_5 ◽

2019 ◽

pp. 133-167

Author(s):

Ahmad Asadi ◽

Reza Safabakhsh

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Deep Learning Architectures

Deep Learning: Concepts and Architectures - Studies in Computational Intelligence ◽

10.1007/978-3-030-31756-0_1 ◽

2019 ◽

pp. 1-24

Author(s):

Mohammad-Parsa Hosseini ◽

Senbao Lu ◽

Kavin Kamaraj ◽

Alexander Slowikowski ◽

Haygreev C. Venkatesh

Keyword(s):

Deep Learning ◽

Learning Architectures

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Assessment of Autoencoder Architectures for Data Representation

Deep Learning: Concepts and Architectures - Studies in Computational Intelligence ◽

10.1007/978-3-030-31756-0_4 ◽

2019 ◽

pp. 101-132

Author(s):

Karishma Pawar ◽

Vahida Z. Attar

Keyword(s):

Data Representation

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Theoretical Characterization of Deep Neural Networks

Deep Learning: Concepts and Architectures - Studies in Computational Intelligence ◽

10.1007/978-3-030-31756-0_2 ◽

2019 ◽

pp. 25-63

Author(s):

Piyush Kaul ◽

Brejesh Lall

Keyword(s):

Neural Networks ◽

Deep Neural Networks ◽

Theoretical Characterization

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Scaling Analysis of Specialized Tensor Processing Architectures for Deep Learning Models

Deep Learning: Concepts and Architectures - Studies in Computational Intelligence ◽

10.1007/978-3-030-31756-0_3 ◽

2019 ◽

pp. 65-99 ◽

Cited By ~ 2

Author(s):

Yuri Gordienko ◽

Yuriy Kochura ◽

Vlad Taran ◽

Nikita Gordienko ◽

Alexandr Rokovyi ◽

...

Keyword(s):

Deep Learning ◽

Scaling Analysis ◽

Learning Models ◽

Processing Architectures

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Using Convolutional Neural Networks to Forecast Sporting Event Results

Deep Learning: Concepts and Architectures - Studies in Computational Intelligence ◽

10.1007/978-3-030-31756-0_9 ◽

2019 ◽

pp. 269-285

Author(s):

Mu-Yen Chen ◽

Ting-Hsuan Chen ◽

Shu-Hong Lin

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Sporting Event

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Deep Neural Networks for Corrupted Labels

Deep Learning: Concepts and Architectures - Studies in Computational Intelligence ◽

10.1007/978-3-030-31756-0_7 ◽

2019 ◽

pp. 211-235

Author(s):

Ishan Jindal ◽

Matthew Nokleby ◽

Daniel Pressel ◽

Xuewen Chen ◽

Harpreet Singh

Keyword(s):

Neural Networks ◽

Deep Neural Networks

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Deep Learning: Concepts and Architectures - Studies in Computational IntelligenceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

Constructing a Convolutional Neural Network with a Suitable Capacity for a Semantic Segmentation Task

Heterogeneous Computing System for Deep Learning

Deep Learning for Learning Graph Representations

The Encoder-Decoder Framework and Its Applications

Deep Learning Architectures

Assessment of Autoencoder Architectures for Data Representation

Theoretical Characterization of Deep Neural Networks

Scaling Analysis of Specialized Tensor Processing Architectures for Deep Learning Models

Using Convolutional Neural Networks to Forecast Sporting Event Results

Deep Neural Networks for Corrupted Labels

Deep Learning: Concepts and Architectures - Studies in Computational Intelligence
Latest Publications