A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z
Sören Weinrich
- ESANN 2023 - Hybrid modelling of dynamic anaerobic digestion process in full-scale with LSTM NN and BMP measurements [Details]
- ESANN 2023 - Robust and Cheap Safety Measure for Exoskeletal Learning Control with Estimated Uniform PAC (EUPAC) [Details]
- ESANN 2016 - Human-centered machine learning through interactive visualization: review and open challenges [Details]
- ESANN 1998 - Introduction to speech recognition using neural networks [Details]
- ESANN 2010 - Adaptive learning rate control for "neural gas principal component analysis" [Details]
- ESANN 2013 - Auto-encoder pre-training of segmented-memory recurrent neural networks [Details]
- ESANN 2016 - Augmenting a convolutional neural network with local histograms - A case study in crop classification from high-resolution UAV imagery [Details]
- ESANN 1999 - Neural field description of state-dependent receptive field changes in the visual cortex [Details]
- ESANN 1998 - Brain-like intelligent control: from neural nets to larger-scale systems [Details]
- ESANN 2014 - FINGeR: Framework for interactive neural-based gesture recognition [Details]
- ESANN 2015 - Dynamic gesture recognition using Echo State Networks [Details]
- ESANN 2015 - Learning objects from RGB-D sensors using point cloud-based neural networks [Details]
- ESANN 2016 - Activity recognition with echo state networks using 3D body joints and objects category [Details]
- ESANN 2016 - Gesture Recognition with a Convolutional Long Short-Term Memory Recurrent Neural Network [Details]
- ESANN 2016 - Learning contextual affordances with an associative neural architecture [Details]
- ESANN 2016 - Semantic Role Labelling for Robot Instructions using Echo State Networks [Details]
- ESANN 2018 - A Sub-Layered Hierarchical Pyramidal Neural Architecture for Facial Expression Recognition [Details]
- ESANN 2018 - An analysis of subtask-dependency in robot command interpretation with dilated CNNs [Details]
- ESANN 2018 - Continuous convolutional object tracking [Details]
- ESANN 2018 - Image-to-Text Transduction with Spatial Self-Attention [Details]
- ESANN 2018 - Inferencing based on unsupervised learning of disentangled representations [Details]
- ESANN 2018 - Slowness-based neural visuomotor control with an Intrinsically motivated Continuous Actor-Critic [Details]
- ESANN 2018 - Surprisal-based activation in recurrent neural networks [Details]
- ESANN 1996 - Towards constructive and destructive dynamic network configuration [Details]
- ESANN 2020 - New Results on Sparse Autoencoders for Posture Classification and Segmentation [Details]
- ESANN 2020 - Self-Organizing Kernel-based Convolutional Echo State Network for Human Actions Recognition [Details]
- ESANN 2021 - Lifelong Learning from Event-based Data [Details]
- ESANN 2021 - Pruning Neural Networks with Supermasks [Details]
- ESANN 2024 - Embodying Language Models in Robot Action [Details]
- ESANN 1998 - Fast orienting movements to visual targets: neural field model of dynamic gaze control [Details]
- ESANN 1993 - Comparison of optimized backpropagation algorithms [Details]
- ESANN 2008 - Discrimination of regulatory DNA by SVM on the basis of over- and under-represented motifs [Details]
- ESANN 2020 - Locally Adaptive Nearest Neighbors [Details]
- ESANN 2006 - Adaptive scene-dependent filters in online learning environments [Details]
- ESANN 2006 - Recent trends in online learning for cognitive robots [Details]
- ESANN 2007 - A hierarchical model for syllable recognition [Details]
- ESANN 2008 - Robust object segmentation by adaptive metrics in Generalized LVQ [Details]
- ESANN 2010 - Figure-ground Segmentation using Metrics Adaptation in Level Set Methods [Details]
- ESANN 2010 - Finding correlations in multimodal data using decomposition approaches [Details]
- ESANN 2014 - Rejection strategies for learning vector quantization [Details]
- ESANN 2015 - Certainty-based prototype insertion/deletion for classification with metric adaptation [Details]
- ESANN 2016 - Choosing the best algorithm for an incremental on-line learning task [Details]
- ESANN 2018 - Efficient accuracy estimation for instance-based incremental active learning [Details]
- ESANN 1999 - Feature binding and relaxation labeling with the competitive layer model [Details]
- ESANN 2000 - A neural network architecture for automatic segmentation of fluorescence micrographs [Details]
- ESANN 2004 - fast bootstrap for least-square support vector machines [Details]
- ESANN 2005 - Non-Euclidean metrics for similarity search in noisy datasets [Details]
- ESANN 2006 - The permutation test for feature selection by mutual information [Details]
- ESANN 2008 - Nonlinear data projection on a sphere with controlled trade-off between trustworthiness and continuity [Details]
- ESANN 1999 - Extraction of intrinsic dimension using CCA - Application to blind sources separation [Details]
- ESANN 2000 - Time series forecasting using CCA and Kohonen maps - application to electricity consumption [Details]
- ESANN 2001 - Input data reduction for the prediction of financial time series [Details]
- ESANN 2003 - Fast approximation of the bootstrap for model selection [Details]
- ESANN 2005 - Generalized Relevance LVQ with Correlation Measures for Biological Data [Details]
- ESANN 2006 - Fuzzy image segmentation with Fuzzy Labelled Neural Gas [Details]
- ESANN 2007 - A neural model of cross-modal association in insects [Details]
- ESANN 2021 - Predicting employee attrition with a more effective use of historical events [Details]
- ESANN 1999 - Support vector machines for multi-class pattern recognition [Details]
- ESANN 1997 - Inductive learning in animat-based neural networks [Details]
- ESANN 2016 - Visualizing stacked autoencoder language learning [Details]
- ESANN 2015 - Pareto Local Search for MOMDP Planning [Details]
- ESANN 2012 - Automatic selection of the number of spatial filters for motor-imagery BCI [Details]
- ESANN 2024 - On the Stability of Neural Segmentation in Radiology [Details]