Buscar
Mostrando ítems 1-10 de 5700
LRP-Based path relevances for global explanation of deep architectures
(Elsevier B.V., 2020)
EM-Based Optimization of Microwave Circuits using Artificial Neural Networks
(IEEE MTT-S Int. Microwave Symp. Workshop Notes and Short Courses, 2013)
Neural networks training using the constructivism paradigms
(1995-12-01)
The Backpropagation Algorithm (BA) is the standard method for training multilayer Artificial Neural Networks (ANN), although it converges very slowly and can stop in a local minimum. We present a new method for neural ...
Neural networks training using the constructivism paradigms
(1995-12-01)
The Backpropagation Algorithm (BA) is the standard method for training multilayer Artificial Neural Networks (ANN), although it converges very slowly and can stop in a local minimum. We present a new method for neural ...
Deep neural network approaches for Spanish sentiment analysis of short texts
(Springer Verlag, 2018)
Sentiment Analysis has been extensively researched in the last years. While important theoretical and practical results have been obtained, there is still room for improvement. In particular, when short sentences and low ...
Self-improving generative artificial neural network for pseudorehearsal incremental class learning
(Algorithms, 2019)
Deep learning models are part of the family of artificial neural networks and, as such, they suffer catastrophic interference when learning sequentially. In addition, the greater number of these models have a rigid ...
Learning styles' recognition in e-learning environments with feed-forward neural networks
(Blackwell Publishing, 2006-05-10)
People have unique ways of learning, which may greatly affect the learning process and, therefore, its outcome. In order to be effective, e-learning systems should be capable of adapting the content of courses to the ...