ICANN 2010 - PDF Preprint Papers

ICANN 2010 International Conference on Artificial Neural Networks

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ICANN
2010
Springer

482views Neural Networks» more ICANN 2010»

Variational Bayesian Image Super-Resolution with GPU Acceleration

14 years 15 days ago

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With the term super-resolution we refer to the problem of reconstructing an image of higher resolution than that of unregistered and degraded observations. Typically, the reconstru...

Giannis K. Chantas

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Id	Views	Title	Status

1	482	Variational Bayesian Image Super-Resolution with GPU Acceleration	claim
2	307	Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines	claim
3	289	On Estimating Mutual Information for Feature Selection	claim
4	288	Neuro-symbolic Representation of Logic Programs Defining Infinite Sets	claim
5	239	Accelerating Large-Scale Convolutional Neural Networks with Parallel Graphics Multiprocessors	claim
6	227	Solving Independent Component Analysis Contrast Functions with Particle Swarm Optimization	claim
7	213	A Learned Saliency Predictor for Dynamic Natural Scenes	claim
8	209	Self-Organization of Steerable Topographic Mappings as Basis for Translation Invariance	claim
9	207	Model of the Hippocampal Learning of Spatio-temporal Sequences	claim
10	204	Action Classification in Soccer Videos with Long Short-Term Memory Recurrent Neural Networks	claim
11	201	Policy Gradients for Cryptanalysis	claim
12	201	Using Evolutionary Multiobjective Techniques for Imbalanced Classification Data	claim
13	199	Deep Bottleneck Classifiers in Supervised Dimension Reduction	claim
14	198	Automatic Segmentation of Color Lip Images Based on Morphological Filter	claim
15	194	Reinforcement Learning Based Neural Controllers for Dynamic Processes without Exploration	claim
16	191	Evaluation of Pooling Operations in Convolutional Architectures for Object Recognition	claim
17	184	Cell Microscopic Segmentation with Spiking Neuron Networks	claim
18	182	How to Use the SOINN Software: User's Guide (Version 1.0)	claim
19	180	Dynamic Shape Learning and Forgetting	claim
20	174	A Directional Laplacian Density for Underdetermined Audio Source Separation	claim
21	173	Visualising Clusters in Self-Organising Maps with Minimum Spanning Trees	claim
22	172	Time Series Forecasting by Evolving Artificial Neural Networks Using "Shuffle", Cross-Validation and Ensembles	claim
23	171	An Artificial Immune Network for Multi-objective Optimization	claim
24	171	Assessing Statistical Reliability of LiNGAM via Multiscale Bootstrap	claim
25	170	A Feature Selection Method for Air Quality Forecasting	claim
26	170	Learning Invariant Visual Shape Representations from Physics	claim
27	169	Kernel-Based Learning from Infinite Dimensional 2-Way Tensors	claim
28	169	Classification Based on Multiple-Resolution Data View	claim
29	167	Designing Simple Nonlinear Filters Using Hysteresis of Single Recurrent Neurons for Acoustic Signal Recognition in Robots	claim
30	166	Exploring Continuous Action Spaces with Diffusion Trees for Reinforcement Learning	claim
31	165	Discovery of Exogenous Variables in Data with More Variables Than Observations	claim
32	164	Multi-Dimensional Deep Memory Atari-Go Players for Parameter Exploring Policy Gradients	claim
33	163	TopoART: A Topology Learning Hierarchical ART Network	claim
34	162	A Bilinear Model for Consistent Topographic Representations	claim
35	157	Using Reinforcement Learning to Guide the Development of Self-organised Feature Maps for Visual Orienting	claim
36	157	Learning in a Unitary Coherent Hippocampus	claim
37	154	Recurrence Enhances the Spatial Encoding of Static Inputs in Reservoir Networks	claim
38	152	Tumble Tree - Reducing Complexity of the Growing Cells Approach	claim
39	152	The Support Feature Machine for Classifying with the Least Number of Features	claim
40	151	Dynamics and Function of a CA1 Model of the Hippocampus during Theta and Ripples	claim
41	150	Teaching Humanoids to Imitate 'Shapes' of Movements	claim
42	149	Sentence Extraction by Graph Neural Networks	claim
43	148	A Cooperative and Penalized Competitive Learning Approach to Gaussian Mixture Clustering	claim
44	147	Computational Properties of Probabilistic Neural Networks	claim
45	138	On the Fringe of Awareness: The Glance-Look Model of Attention-Emotion Interactions	claim
46	133	Shape-Based Tumor Retrieval in Mammograms Using Relevance-Feedback Techniques	claim
47	126	Self-Organizing Incremental Neural Network and Its Application	claim
48	123	Autonomous Generation of Internal Representations for Associative Learning	claim
49	106	Unsupervised Learning of Relations	claim

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