367 citations · 1.3k across the 29 of their papers we have counts for
7 papers · 1 filter
The Six Fronts of the Generative Adversarial Networks
Alceu Bissoto, Eduardo Valle, Sandra Avila
Generative Adversarial Networks fostered a newfound interest in generative models, resulting in a swelling wave of new works that new-coming researchers may find formidable to surf…
Grape detection, segmentation and tracking using deep neural networks and three-dimensional association
Thiago T. Santos, Leonardo L. de Souza, Andreza A. dos Santos +1
Agricultural applications such as yield prediction, precision agriculture and automated harvesting need systems able to infer the crop state from low-cost sensing devices. Proximal…
Handling Inter-Annotator Agreement for Automated Skin Lesion Segmentation
Vinicius Ribeiro, Sandra Avila, Eduardo Valle
In this work, we explore the issue of the inter-annotator agreement for training and evaluating automated segmentation of skin lesions. We explore what different degrees of agreeme…
Solo or Ensemble? Choosing a CNN Architecture for Melanoma Classification
Fábio Perez, Sandra Avila, Eduardo Valle
Convolutional neural networks (CNNs) deliver exceptional results for computer vision, including medical image analysis. With the growing number of available architectures, picking…
Combating the Elsagate phenomenon: Deep learning architectures for disturbing cartoons
Akari Ishikawa, Edson Bollis, Sandra Avila
Watching cartoons can be useful for children's intellectual, social and emotional development. However, the most popular video sharing platform today provides many videos with Elsa…
(De)Constructing Bias on Skin Lesion Datasets
Alceu Bissoto, Michel Fornaciali, Eduardo Valle +1
Melanoma is the deadliest form of skin cancer. Automated skin lesion analysis plays an important role for early detection. Nowadays, the ISIC Archive and the Atlas of Dermoscopy da…
Skin Lesion Synthesis with Generative Adversarial Networks
Alceu Bissoto, Fábio Perez, Eduardo Valle +1
Skin cancer is by far the most common type of cancer. Early detection is the key to increase the chances for successful treatment significantly. Currently, Deep Neural Networks are…