most citedPhrase-based Image Captioning

50 citations · 104 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL201550 cited

Phrase-based Image Captioning

Rémi Lebret, Pedro O. Pinheiro, Ronan Collobert

Generating a novel textual description of an image is an interesting problem that connects computer vision and natural language processing. In this paper, we present a simple model…

cs.CL201429 cited

Simple Image Description Generator via a Linear Phrase-Based Approach

Remi Lebret, Pedro O. Pinheiro, Ronan Collobert

Generating a novel textual description of an image is an interesting problem that connects computer vision and natural language processing. In this paper, we present a simple model…

cs.LG20141 cited

Learning linearly separable features for speech recognition using convolutional neural networks

Dimitri Palaz, Mathew Magimai Doss, Ronan Collobert

Automatic speech recognition systems usually rely on spectral-based features, such as MFCC of PLP. These features are extracted based on prior knowledge such as, speech perception…

cs.LG20146 cited

Joint RNN-Based Greedy Parsing and Word Composition

Joël Legrand, Ronan Collobert

This paper introduces a greedy parser based on neural networks, which leverages a new compositional sub-tree representation. The greedy parser and the compositional procedure are j…

cs.CL20144 cited

N-gram-Based Low-Dimensional Representation for Document Classification

Rémi Lebret, Ronan Collobert

The bag-of-words (BOW) model is the common approach for classifying documents, where words are used as feature for training a classifier. This generally involves a huge number of f…

cs.CL20142 cited

Rehabilitation of Count-based Models for Word Vector Representations

Rémi Lebret, Ronan Collobert

Recent works on word representations mostly rely on predictive models. Distributed word representations (aka word embeddings) are trained to optimally predict the contexts in which…