3 citations · 11 across the 4 of their papers we have counts for
9 papers
scikit-dyn2sel -- A Dynamic Selection Framework for Data Streams
Lucca Portes Cavalheiro, Jean Paul Barddal, Alceu de Souza Britto +1
Mining data streams is a challenge per se. It must be ready to deal with an enormous amount of data and with problems not present in batch machine learning, such as concept drift.…
Random Forest for Dissimilarity-based Multi-view Learning
Simon Bernard, Hongliu Cao, Robert Sabourin +1
Many classification problems are naturally multi-view in the sense their data are described through multiple heterogeneous descriptions. For such tasks, dissimilarity strategies ar…
A Novel Random Forest Dissimilarity Measure for Multi-View Learning
Hongliu Cao, Simon Bernard, Robert Sabourin +1
Multi-view learning is a learning task in which data is described by several concurrent representations. Its main challenge is most often to exploit the complementarities between t…
Deep Learning Approaches for Image Retrieval and Pattern Spotting in Ancient Documents
Kelly Lais Wiggers, Alceu de Souza Britto Junior, Alessandro Lameiras Koerich +2
This paper describes two approaches for content-based image retrieval and pattern spotting in document images using deep learning. The first approach uses a pre-trained CNN model t…
Image Retrieval and Pattern Spotting using Siamese Neural Network
Kelly L. Wiggers, Alceu S. Britto, Laurent Heutte +2
This paper presents a novel approach for image retrieval and pattern spotting in document image collections. The manual feature engineering is avoided by learning a similarity-base…
Pattern Spotting in Historical Documents Using Convolutional Models
Ignacio Úbeda, Jose M. Saavedra, Stéphane Nicolas +2
Pattern spotting consists of searching in a collection of historical document images for occurrences of a graphical object using an image query. Contrary to object detection, no pr…