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Neural Information Processing|Tom Gedeon

Neural Information Processing : 26th International Conference, Iconip 2019, Sydney, Nsw, Australia, December 12-15, 2019, Proceedings, Part I

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Overview

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 Knowledge Transfer.- An Analysis of the Interaction Between Transfer Learning Protocols in Deep Neural Networks.- Feature Learning and Representation.- Representation Learning for Heterogeneous Information Networks via Embedding Events.- Unified Framework for Visual Domain Adaptation Using Globality- Locality Preserving Projections.- Zero-shot Learning for Intrusion Detection via Attribute Representation.- Region Selection Model with Saliency Constraint for Fine-grained Recognition.- Siamese Net based Feature Learning for IDS.- Self-Attentive Pyramid Network for Single Image De-raining.- Human Centred Computing.- Feature Fusion Based Deep Spatiotemporal Model for Violence Detection in Videos.- Learning to Navigate in Human Environments via Deep Reinforcement Learning.- An Effective Yawn Behavior Detection Method in Classroom.- Bidirectional LSTM with MFCC Feature Extraction for Sleep Arousal Detection in Multi-channel Signal Data.- Development of Biomedical Corpus Enlargement Platform Using BERT for Bio-entity Recognition.- A Generative Face Completion Method Based on Associative Memory.- White-Box Target Attack for EEG-Based BCI Regression Problems.- Human Centred Computing and Medicine.- Real-time Guidewire Segmentation and Tracking in Endovascular Aneurysm Repair.- Infra-slow Electroencephalogram Power is Associated with Reaction Time in Simple Discrimination Tasks.- Classifying Speech Data in Parkinson's Disease Based on Class Probability Output Networks.- ConvCaps: Multi-input capsule network for brain tumor classification.- G-ResNet: Improved ResNet for brain tumor classification.- Affinity Graph based End-to-End Deep Convolutional Networks for CT Hemorrhage Segmentation.- On the Stability of a Pass-thought Security System in Different Brain States.- Brain network decomposition by Auto Encoder (AE) and Graph Auto Encoder (GAE).- Hybrid Models.- Accelerated training algorithms of general fuzzy min-max neural network using GPU for very

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Details

  • ISBN-13: 9783030367077
  • ISBN-10: 303036707X
  • Publisher: Springer
  • Publish Date: December 2019
  • Dimensions: 9.21 x 6.14 x 1.6 inches
  • Shipping Weight: 2.43 pounds
  • Page Count: 781

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