175 citations · 450 across the 16 of their papers we have counts for
15 papers · 1 filter
Building Brain Tumor Segmentation Networks with User-Assisted Filter Estimation and Selection
Matheus A. Cerqueira, Flávia Sprenger, Bernardo C. A. Teixeira +1
Brain tumor image segmentation is a challenging research topic in which deep-learning models have presented the best results. However, the traditional way of training those models…
Efficient Multiscale Object-based Superpixel Framework
Felipe Belém, Benjamin Perret, Jean Cousty +2
Superpixel segmentation can be used as an intermediary step in many applications, often to improve object delineation and reduce computer workload. However, classical methods do no…
Intestinal Parasites Classification Using Deep Belief Networks
Mateus Roder, Leandro A. Passos, Luiz Carlos Felix Ribeiro +3
Currently, approximately billion people are infected by intestinal parasites worldwide. Diseases caused by such infections constitute a public health problem in most tropical c…
Automated Diagnosis of Intestinal Parasites: A new hybrid approach and its benefits
D. Osaku, C. F. Cuba, Celso T. N. Suzuki +2
Intestinal parasites are responsible for several diseases in human beings. In order to eliminate the error-prone visual analysis of optical microscopy slides, we have investigated…
Convolutional Neural Networks from Image Markers
Barbara C. Benato, Italos E. de Souza, Felipe L. Galvão +1
A technique named Feature Learning from Image Markers (FLIM) was recently proposed to estimate convolutional filters, with no backpropagation, from strokes drawn by a user on very…
Deploying machine learning to assist digital humanitarians: making image annotation in OpenStreetMap more efficient
John E. Vargas-Muñoz, Devis Tuia, Alexandre X. Falcão
Locating populations in rural areas of developing countries has attracted the attention of humanitarian mapping projects since it is important to plan actions that affect vulnerabl…