Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions

1. Workshop: Reservoir Computing - Physical Implementations

   1. Optoelectronic Reservoir Computing Using a Mixed Digital-Analog Hardware Implementation

      • Miguel C. Soriano, Pau Massuti-Ballester, Jesús Yelo, Ingo Fischer

      Pages 170-174

   2. Comparison of Feature Extraction Techniques for Handwritten Digit Recognition with a Photonic Reservoir Computer

      • Piotr Antonik, Nicolas Marsal, Daniel Brunner, Damien Rontani

      Pages 175-179

   3. Polarization Dynamics of VCSELs Improves Reservoir Computing Performance

      • Jeremy Vatin, Damien Rontani, Marc Sciamanna

      Pages 180-183

   4. Reservoir-Size Dependent Learning in Analogue Neural Networks

      • Xavier Porte, Louis Andreoli, Maxime Jacquot, Laurent Larger, Daniel Brunner

      Pages 184-192

   5. Transferring Reservoir Computing: Formulation and Application to Fluid Physics

      • Masanobu Inubushi, Susumu Goto

      Pages 193-199

2. Special Session: Artificial Intelligence in Medicine

   1. Front Matter

      Pages 201-204

      PDF

   2. Investigation of EEG-Based Graph-Theoretic Analysis for Automatic Diagnosis of Alcohol Use Disorder

      • Wajid Mumtaz, Lukáš Vařeka, Roman Mouček

      Pages 205-218

   3. EchoQuan-Net: Direct Quantification of Echo Sequence for Left Ventricle Multidimensional Indices via Global-Local Learning, Geometric Adjustment and Multi-target Relation Learning

      • Rongjun Ge, Guanyu Yang, Chenchu Xu, Jiulou Zhang, Yang Chen, Limin Luo et al.

      Pages 219-230

   4. An Attention-Based ID-CNNs-CRF Model for Named Entity Recognition on Clinical Electronic Medical Records

      • Ming Gao, Qifeng Xiao, Shaochun Wu, Kun Deng

      Pages 231-242

   5. Deep Text Prior: Weakly Supervised Learning for Assertion Classification

      • Vadim Liventsev, Irina Fedulova, Dmitry Dylov

      Pages 243-257

   6. Inter-region Synchronization Analysis Based on Heterogeneous Matrix Similarity Measurement

      • Hengjin Ke, Dan Chen, Lei Zhang, XinHua Zhang, Xianzeng Liu, Xiaoli Li

      Pages 258-272

   7. Bi-ResNet: Fully Automated Classification of Unregistered Contralateral Mammograms

      • Runze Wang, Yanan Guo, Wendao Wang, Yide Ma

      Pages 273-283

   8. Pattern Recognition for COPD Diagnostics Using an Artificial Neural Network and Its Potential Integration on Hardware-Based Neuromorphic Platforms

      • Pouya Soltani Zarrin, Christian Wenger

      Pages 284-288

   9. Quantifying Structural Heterogeneity of Healthy and Cancerous Mitochondria Using a Combined Segmentation and Classification USK-Net

      • Manish Mishra, Sabine Schmitt, Hans Zischka, Michael Strasser, Nassir Navab, Carsten Marr et al.

      Pages 289-298

   10. Breast Cancer Classification on Histopathological Images Affected by Data Imbalance Using Active Learning and Deep Convolutional Neural Network

       • Bogdan Kwolek, Michał Koziarski, Andrzej Bukała, Zbigniew Antosz, Bogusław Olborski, Paweł Wąsowicz et al.

       Pages 299-312

   11. Measuring the Angle of Hallux Valgus Using Segmentation of Bones on X-Ray Images

       • Konrad Kwolek, Henryk Liszka, Bogdan Kwolek, Artur Gądek

       Pages 313-325

   12. Human Body Posture Recognition Using Wearable Devices

       • Junxiu Liu, Mingxing Li, Yuling Luo, Su Yang, Senhui Qiu

       Pages 326-337

   13. Collaborative Denoising Autoencoder for High Glycated Haemoglobin Prediction

       • Zakhriya Alhassan, David Budgen, Ali Alessa, Riyad Alshammari, Tahani Daghstani, Noura Al Moubayed

       Pages 338-350

3. Special Session: Informed and Explainable Methods for Machine Learning

   1. Front Matter

      Pages 351-352

      PDF

   2. On Chow-Liu Forest Based Regularization of Deep Belief Networks

      • Alex Sarishvili, Andreas Wirsen, Mats Jirstrand

      Pages 353-364

The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions. 

• artificial intelligence
• classification
• clustering
• computer networks
• echo state networks
• image processing
• image reconstruction
• image segmentation
• learning algorithms
• machine learning
• neural networks
• optical communication
• photonics
• recurrent neural networks
• Reservoir Computing
• semantics
• signal processing
• Support Vector Machines (SVM)
• telecommunication networks
• telecommunication traffic
• algorithm analysis and problem complexity

• Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany

  Igor V. Tetko, Pavel Karpov, Fabian Theis

• Institute of Computer Science, Czech Academy of Sciences, Prague 8, Czech Republic

  Věra Kůrková

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