Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions
Springer International Publishing (Verlag)
978-3-030-30492-8 (ISBN)
A Reservoir Computing Framework for Continuous Gesture Recognition.- Using conceptors to transfer between long-term and short-term Memory.- Bistable Perception in Conceptor Networks.- Continual Learning exploiting Structure of Fractal Reservoir Computing.- Continuous Blood Pressure Estimation through Optimized Echo State Networks.- Reservoir Topology in Deep Echo State Networks.- Multiple Pattern Generations and Chaotic Itinerant dynamics in Reservoir Computing.- Echo State Network with Adversarial Training.- Hyper-spherical reservoirs for Echo State Networks.- Echo State vs. LSTM Networks for Word Sense Disambiguation.- Echo State Networks for Named Entity Recognition.- Efficient Cross-Validation of Echo State Networks.- Echo State Property of Neuronal Cell Cultures.- Overview on the PHRESCO project: PHotonic REServoir COmputing.- Classification of Human Actions in Videos with a Large-Scale Photonic Reservoir Computer.- A power-effcient architecture for on-chip reservoir computing.- Time Series Processing with VCSEL-based Reservoir Computer.- Optoelectronic reservoir computing using a mixed digital-analog hardware implementation.- Comparison of Feature Extraction Techniques for Handwritten Digit Recognition with a Photonic Reservoir Computer.- Polarization dynamics of VCSELs improves reservoir computing performance..- Reservoir-size dependent learning in analogue neural networks.- Transferring reservoir computing: formulation and application to fluid physics.- Investigation of EEG-based Graph-theoretic Analysis for Automatic Diagnosis of Alcohol Use Disorder .- EchoQuan-Net: Direct Quantification of Echo Sequence for Left Ventricle Multidimensional Indices via Global-Local Learning, Geometric Adjustment, and multi-target relation learning.- An attention-based ID-CNNs-CRF model for named entity recognition on clinical electronic medical records.- Deep Text Prior: Weakly Supervised Learning for Assertion Classification.- Inter-region SynchronizationAnalysis based on Heterogeneous Matrix Similarity Measurement.- Bi-ResNet: Fully automated classification of unregistered contralateral mammograms.- Pattern Recognition for COPD Diagnostics Using an Artificial Neural Network and Its Potential Integration on Hardware-based Neuromorphic Platforms.- Quantifying Structural Heterogeneity of Healthy and Cancerous Mitochondria using a Combined Segmentation and Classification USK-Net.- Breast Cancer Classification on Histopathological Images Affected by Data Imbalance Using Active Learning and Deep Convolutional Neural Network.- Measuring the Angle of Hallux Valgus Using Segmentation of Bones on X-ray Images.- Human Body Posture Recognition Using Wearable Devices.- Collaborative Denoising Autoencoder for High Glycated Haemoglobin Prediction.- On Chow-Liu forest based regularization of deep belief networks.- Prototypes within Minimum Enclosing Balls.- Exploring Local Transformation Shared Weights in Convolutional Neural Networks.- The Good, theBad and the Ugly: augmenting a black-box model with expert knowledge.- Hierarchical Attentional Hybrid Neural Networks for Document Classification.- Reinforcement learning informed by optimal control.- Explainable Anomaly Detection via Feature-Based Localization.- Bayesian Automatic Relevance Determination for Feature selection in Credit Default Modelling.- TSXplain: Demystification of DNN Decisions for Time-Series using Natural Language and Statistical Features.- DeepMimic: Mentor-Student Unlabeled Data Based Training.- Evaluation of tag clusterings for user profiling in movie recommendation.- A Sparse Filtering-based Approach for Non-Blind Deep Image Denoising.- Hybrid Attention Driven Text-to-Image Synthesis via Generative Adversarial Networks.- Hypernetwork functional image representation.- Instance-based Segmentation for Boundary Detection of Neuropathic Ulcers through Mask-RCNN.- Capsule Networks for attention under occlusion.- IP-GAN: Learning Identity and Pose Disentanglementin
| Erscheinungsdatum | 13.09.2019 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science | Theoretical Computer Science and General Issues |
| Zusatzinfo | XXXII, 852 p. 295 illus., 211 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 1329 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Schlagworte | Algorithm analysis and problem complexity • Applications • Artificial Intelligence • classification • Clustering • Computer Networks • Computer Science • conference proceedings • echo state networks • Image Processing • image reconstruction • Image Segmentation • Informatics • Learning Algorithms • machine learning • Neural networks • Optical communication • Photonics • Recurrent Neural Networks • Research • reservoir computing • Semantics • Signal Processing • Support Vector Machines (SVM) • Telecommunication networks • telecommunication traffic |
| ISBN-10 | 3-030-30492-2 / 3030304922 |
| ISBN-13 | 978-3-030-30492-8 / 9783030304928 |
| Zustand | Neuware |
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