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
Victor Amaral De Sousa
- ESANN 2018 - Structuring and Solving Multi-Criteria Decision Making Problems using Artificial Neural Networks: a smartphone recommendation case [Details]
- ESANN 1997 - Nonlinearity and separation capability: further justification for the ICA algorithm with a learned mixture of parametric densities [Details]
- ESANN 2016 - Maximum likelihood learning of RBMs with Gaussian visible units on the Stiefel manifold [Details]
- ESANN 2003 - On different ensembles of kernel machines [Details]
- ESANN 2023 - Real-time Detection of Evoked Potentials by Deep Learning: a Case Study [Details]
- ESANN 2020 - On Feature Selection Using Anisotropic General Regression Neural Network [Details]
- ESANN 2012 - Range-based non-orthogonal ICA using cross-entropy method [Details]
- ESANN 2026 - Hybrid-AIRL: Enhancing Inverse Reinforcement Learning with Supervised Expert Guidance [Details]
- ESANN 2023 - Mixture of stochastic block models for multiview clustering [Details]
- ESANN 2018 - Spatial pooling as feature selection method for object recognition [Details]
- ESANN 2023 - TabSRA: An Attention based Self-Explainable Model for Tabular Learning [Details]
- ESANN 2023 - Multimodal Approach for Harmonized System Code Prediction [Details]
- ESANN 2023 - Similarity versus Supervision: Best Approaches for HS Code Prediction [Details]
- ESANN 2017 - Structure optimization for deep multimodal fusion networks using graph-induced kernels [Details]
- ESANN 2002 - Prediction of mental development of preterm newborns at birth time using LS-SVM [Details]
- ESANN 2004 - input arrival-time-dependent decoding scheme for a spiking neural network [Details]
- ESANN 2009 - A self-training method for learning to rank with unlabeled data [Details]
- ESANN 2009 - Sparse differential connectivity graph of scalp EEG for epileptic patients [Details]
- ESANN 2025 - Membership Inference Attack in Random Forests [Details]
- ESANN 2026 - Lightweight Personalisation for MEMS-Based Wearables: A Padel Stroke Recognition Case Study [Details]
- ESANN 2026 - On the Importance of Time Constants in Spiking Neural Networks [Details]
- ESANN 2012 - Supervised and unsupervised classification approaches for human activity recognition using body-mounted sensors [Details]
- ESANN 2018 - CDTW-based classification for Parkinson's Disease diagnosis [Details]
- ESANN 2024 - Multidimensional CDTW-based features for Parkinson's Disease classification [Details]
- ESANN 2025 - Semantic Segmentation for Waterbody Extraction Using Superpixels and Convolutional Neural Networks Classifier [Details]
- ESANN 2026 - Alignment of Islamic Legal Texts [Details]
- ESANN 2010 - A Novel Two-Phase SOM Clustering Approach to Discover Visitor Interests in a Website [Details]
- ESANN 2001 - Extracting motion information using a biologically realistic model retina [Details]
- ESANN 2018 - Interpreting deep learning models for ordinal problems [Details]
- ESANN 2018 - Order Crossover for the Inventory Routing Problem [Details]
- ESANN 2007 - Transition from initialization to working stage in biologically realistic networks [Details]
- ESANN 2004 - A New Learning Rates Adaptation Strategy for the Resilient Propagation Algorithm [Details]
- ESANN 1997 - Sequential hypotheses tests for modelling neural networks [Details]
- ESANN 2017 - Prediction of preterm infant mortality with Gaussian process classification [Details]
- ESANN 2019 - Deep RL for autonomous robots: limitations and safety challenges [Details]