Background Over the last years Deep Learning has shown to yield remarkable results when
compared to traditional computer vision algorithms, in a large variety of computer vision …

This paper proposes HeteroG, an automatic module to accelerate deep neural network
training in heterogeneous GPU clusters. To train a deep learning model with large amounts …

This document describes the details and the motivation behind a new dataset we collected
for the semi-supervised recognition challenge~\cite {semi-aves} at the FGVC7 workshop at …

In this article, we exploit Semi-Supervised Learning (SSL) to increase the amount of training
data to improve the performance of Fine-Grained Visual Categorization (FGVC). This …

Learning from hybrid labels is suitable for dealing with the real-world scenario, where the
labels of the training dataset include fine-grained labels and coarse-grained labels …

Learning with weak supervision already becomes one of the research trends in fine-grained
image recognition. These methods aim to learn feature representation in the case of less …