Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 1 of 1
Full-Text Articles in Computer Sciences
Analysing The Effects Of Data Augmentation And Free Parameters For Text Classification With Recurrent Convolutional Neural Networks, Jonathan Quijas
Analysing The Effects Of Data Augmentation And Free Parameters For Text Classification With Recurrent Convolutional Neural Networks, Jonathan Quijas
Open Access Theses & Dissertations
Convolutional neural networks have seen much success in computer vision and natural language processing tasks. When training convolutional neural networks for text classification tasks, a common technique is to transform an input sequence of words into a dense matrix of word embeddings, or words represented as dense vectors, using table lookup operations. This enables the inputs to be represented in a way that the well-known convolution/pooling operations can be applied to them in a manner similar to images. These word embeddings may be further incorporated into the neural network itself as a trainable layer to allow fine-tuning, usually leading to …