105 citations · 248 across the 11 of their papers we have counts for
15 papers
CIDEr-R: Robust Consensus-based Image Description Evaluation
Gabriel Oliveira dos Santos, Esther Luna Colombini, Sandra Avila
This paper shows that CIDEr-D, a traditional evaluation metric for image description, does not work properly on datasets where the number of words in the sentence is significantly…
GAN-Based Data Augmentation and Anonymization for Skin-Lesion Analysis: A Critical Review
Alceu Bissoto, Eduardo Valle, Sandra Avila
Despite the growing availability of high-quality public datasets, the lack of training samples is still one of the main challenges of deep-learning for skin lesion analysis. Genera…
Less is More: Sample Selection and Label Conditioning Improve Skin Lesion Segmentation
Vinicius Ribeiro, Sandra Avila, Eduardo Valle
Segmenting skin lesions images is relevant both for itself and for assisting in lesion classification, but suffers from the challenge in obtaining annotated data. In this work, we…
Debiasing Skin Lesion Datasets and Models? Not So Fast
Alceu Bissoto, Eduardo Valle, Sandra Avila
Data-driven models are now deployed in a plethora of real-world applications - including automated diagnosis - but models learned from data risk learning biases from that same data…
Weakly Supervised Learning Guided by Activation Mapping Applied to a Novel Citrus Pest Benchmark
Edson Bollis, Helio Pedrini, Sandra Avila
Pests and diseases are relevant factors for production losses in agriculture and, therefore, promote a huge investment in the prevention and detection of its causative agents. In m…
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…