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Intelligence Science and Big Data Engineering. Big Data and Machine Learning

9th International Conference, IScIDE 2019, Nanjing, China, October 17–20, 2019, Proceedings, Part II

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. Zhen Cui

    1. Nanjing University of Science and Technology, Nanjing, China

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  2. Jinshan Pan

    1. Nanjing University of Science and Technology, Nanjing, China

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  3. Shanshan Zhang

    1. Nanjing University of Science and Technology, Nanjing, China

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  4. Liang Xiao

    1. Nanjing University of Science and Technology, Nanjing, China

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  5. Jian Yang

    1. Nanjing University of Science and Technology, Nanjing, China

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11936)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: IScIDE 2019.

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About this book

The two volumes LNCS 11935 and 11936 constitute the proceedings of the 9th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2019, held in Nanjing, China, in October 2019.

The 84 full papers presented were carefully reviewed and selected from 252 submissions.The papers are organized in two parts: visual data engineering; and big data and machine learning. They cover a large range of topics including information theoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics, bioinformatics, computational biology and brain-computer interfaces, as well as advances in fundamental pattern recognition techniques relevant to image processing, computer vision and machine learning.

 


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Keywords

Table of contents (37 papers)

  1. Front Matter

    Pages i-xx
    Download chapter PDF

  2. Analysis of WLAN’s Receiving Signal Strength Indication for Indoor Positioning

    • Minmin Lin, Zhisen Wei, Baoxing Chen, Wenjie Zhang, Jingmin Yang
    Pages 1-14

  3. Computational Decomposition of Style for Controllable and Enhanced Style Transfer

    • Minchao Li, Shikui Tu, Lei Xu
    Pages 15-39

  4. Laplacian Welsch Regularization for Robust Semi-supervised Dictionary Learning

    • Jingchen Ke, Chen Gong, Lin Zhao
    Pages 40-52

  5. Non-local MMDenseNet with Cross-Band Features for Audio Source Separation

    • Yi Huang
    Pages 53-64

  6. A New Method of Metaphor Recognition for A-is-B Model in Chinese Sentences

    • Wei-min Wang, Rong-rong Gu, Shou-fu Fu, Dong-sheng Wang
    Pages 65-77

  7. Layerwise Recurrent Autoencoder for Real-World Traffic Flow Forecasting

    • Junhui Zhao, Tianqi Zhu, Ruidong Zhao, Peize Zhao
    Pages 78-88

  8. Mining Meta-association Rules for Different Types of Traffic Accidents

    • Ziyu Zhao, Weili Zeng, Zhengfeng Xu, Zhao Yang
    Pages 89-100

  9. Reliable Domain Adaptation with Classifiers Competition

    • Jingru Fu, Lei Zhang
    Pages 101-113

  10. An End-to-End LSTM-MDN Network for Projectile Trajectory Prediction

    • Li-he Hou, Hua-jun Liu
    Pages 114-125

  11. DeepTF: Accurate Prediction of Transcription Factor Binding Sites by Combining Multi-scale Convolution and Long Short-Term Memory Neural Network

    • Xiao-Rong Bao, Yi-Heng Zhu, Dong-Jun Yu
    Pages 126-138

  12. Epileptic Seizure Prediction Based on Convolutional Recurrent Neural Network with Multi-Timescale

    • Lijuan Duan, Jinze Hou, Yuanhua Qiao, Jun Miao
    Pages 139-150

  13. L2R-QA: An Open-Domain Question Answering Framework

    • Tieke He, Yu Li, Zhipeng Zou, Qing Wu
    Pages 151-162

  14. Attention Relational Network for Few-Shot Learning

    • Jia Shuai, JiaMing Chen, Meng Yang
    Pages 163-174

  15. Syntactic Analysis of Power Grid Emergency Pre-plans Based on Transfer Learning

    • He Shi, Qun Yang, Bo Wang, Shaohan Liu, Kai Zhou
    Pages 175-186

  16. Improved CTC-Attention Based End-to-End Speech Recognition on Air Traffic Control

    • Kai Zhou, Qun Yang, XiuSong Sun, ShaoHan Liu, JinJun Lu
    Pages 187-196

  17. Revisit Lmser from a Deep Learning Perspective

    • Wenjin Huang, Shikui Tu, Lei Xu
    Pages 197-208

  18. A New Network Traffic Identification Base on Deep Factorization Machine

    • Zhenxing Xu, Junyi Zhang, Daoqiang Zhang, Hanyu Wei
    Pages 209-218

  19. 3Q: A 3-Layer Semantic Analysis Model for Question Suite Reduction

    • Wei Dai, Siyuan Sheni, Tieke Hei
    Pages 219-231

  20. Data Augmentation for Deep Learning of Judgment Documents

    • Ge Yan, Yu Li, Shu Zhang, Zhenyu Chen
    Pages 232-242
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Other volumes

  1. Intelligence Science and Big Data Engineering. Visual Data Engineering

  2. Intelligence Science and Big Data Engineering. Big Data and Machine Learning

Editors and Affiliations

  • Nanjing University of Science and Technology, Nanjing, China

    Zhen Cui, Jinshan Pan, Shanshan Zhang, Liang Xiao, Jian Yang

Bibliographic Information

  • Book Title: Intelligence Science and Big Data Engineering. Big Data and Machine Learning

  • Book Subtitle: 9th International Conference, IScIDE 2019, Nanjing, China, October 17–20, 2019, Proceedings, Part II

  • Editors: Zhen Cui, Jinshan Pan, Shanshan Zhang, Liang Xiao, Jian Yang

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-030-36204-1

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer Nature Switzerland AG 2019

  • Softcover ISBN: 978-3-030-36203-4Published: 29 November 2019

  • eBook ISBN: 978-3-030-36204-1Published: 28 November 2019

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XX, 455

  • Number of Illustrations: 212 b/w illustrations, 145 illustrations in colour

  • Topics: Image Processing and Computer Vision, Artificial Intelligence, Data Mining and Knowledge Discovery, Models and Principles

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