The effect of spatial RNNs on neural network feature maps
Study of LSTMs for feature correlation in order to improve generalization of networks when training data is not abundant.
| Autor: | |
|---|---|
| Tipo de documento: | dissertação |
| Data de publicação: | 2018 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositório: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglês |
| OAI Identifier: | oai:upcommons.upc.edu:2117/127074 |
| Acesso em linha: | https://hdl.handle.net/2117/127074 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Neural networks (Computer science) Machine learning LSTM RNN feature maps machine learning deep learning computer vision learning rate robustness spatial RNN GRU neural networks Xarxes neuronals (Informàtica) Aprenentatge automàtic Àrees temàtiques de la UPC::Enginyeria de la telecomunicació |
| Resumo: | Study of LSTMs for feature correlation in order to improve generalization of networks when training data is not abundant. |
|---|