rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Neural Information Processing
    sub title: 26th International Conference, ICONIP 2019, Sydney, NSW, Australia, December 12-15, 2019, Proceedings, Part I
  name:
    name part: Gedeon, Tom.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Wong, Kok Wai.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Lee, Minho.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XXII, 781 p. 318 illus., 234 illus. in color. online resource.
  abstract: The three-volume set of LNCS 11953, 11954, and 11955 constitutes the proceedings of the 26th International Conference on Neural Information Processing, ICONIP 2019, held in Sydney, Australia, in December 2019. The 173 full papers presented were carefully reviewed and selected from 645 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The first volume, LNCS 11953, is organized in topical sections on adversarial networks and learning; convolutional neural networks; deep neural networks; feature learning and representation; human centred computing; human centred computing and medicine; hybrid models; and artificial intelligence and cybersecurity.
  table of contents: Adversarial Networks and Learning -- FH-GAN: Face Hallucination and Recognition using Generative Adversarial Network -- Adversarial Learning for Cross-modal Retrieval with Wasserstein Distance -- Reducing the Subject Variability of EEG Signals with Adversarial Domain Generalization -- Multi-View Image Generation by Cycle CVAE-GAN Networks -- B-DCGAN: Evaluation of Binarized DCGAN for FPGA -- A Natural Scene Text Extraction Approach Based on Generative Adversarial Learning -- Weakly Supervised Fine-Grained Visual Recognition via Adversarial Complementary Attentions and Hierarchical Bilinear Pooling -- Learning an Adversarial Network for Speech Enhancement under Extremely Low Signal-to-noise Ratio Condition -- HaGAN: hierarchical attentive adversarial learning for task-oriented dialogue system -- Learning to Generate Ambiguous Sequences -- Convolutional Neural Networks -- Deep Learning for Combo Object Detection -- DasNet: Dynamic Adaptive Structure for Accelerating Multi-Task Convolutional Neural Network -- Confusion-Aware Convolutional Neural Network for Image Classification -- Feature Learning and Data Compression of Biosignals Using Convolutional Autoencoders for Sleep Apnea Detection -- Self-Adaptive Network Pruning -- Text-Augmented Knowledge Representation Learning Based on Convolutional Network -- A novel online ensemble convolutional neural networks for streaming data -- Cross-Media Image-Text Retrieval Based on Two-Level Network -- Fusion Convolutional Attention Network for Opinion Spam Detection -- Deep CNN Based System for Detection and Evaluation of RoIs in Flooded Areas -- Deep Neural Networks -- Improving Deep Learning by Regularized Scale-free MSE of Representations -- Training behavior of deep neural network in frequency domain -- On The Initialization of Long Short-Term Memory Networks -- A Multi-cascaded Deep Model for Bilingual SMS Classification -- Low Resource Named Entity Recognition using Contextual Word Representation and Neural Cross-Lingual …
  note: edited by Tom Gedeon, Kok Wai Wong, Minho Lee.
  subject:
    topic: Pattern recognition
  subject:
    topic: Artificial intelligence
  subject:
    topic: Optical data processing
  subject:
    topic: Application software
  subject:
    topic: Special purpose computers
  subject:
    topic: Pattern Recognition
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Image Processing and Computer Vision
  subject:
    topic: Information Systems Applications (incl. Internet)
  subject:
    topic: Special Purpose and Application-Based Systems
  classification: Q337.5
  classification: TK7882.P3
  classification: 006.4
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Theoretical Computer Science and General Issues ; 11953
  identifier: 9783030367084
  identifier: https://doi.org/10.1007/978-3-030-36708-4
  record info:
    record creation date: 191212
    record change date: 20191212075105.0
    record identifier: 978-3-030-36708-4