Search Results for author: Michel Fornaciali

Found 7 papers, 5 papers with code

(De)Constructing Bias on Skin Lesion Datasets

1 code implementation18 Apr 2019 Alceu Bissoto, Michel Fornaciali, Eduardo Valle, Sandra Avila

We fed models with additional clinically meaningful information, which failed to improve the results even slightly, suggesting the destruction of cogent correlations.

Deep-Learning Ensembles for Skin-Lesion Segmentation, Analysis, Classification: RECOD Titans at ISIC Challenge 2018

no code implementations25 Aug 2018 Alceu Bissoto, Fábio Perez, Vinícius Ribeiro, Michel Fornaciali, Sandra Avila, Eduardo Valle

This extended abstract describes the participation of RECOD Titans in parts 1 to 3 of the ISIC Challenge 2018 "Skin Lesion Analysis Towards Melanoma Detection" (MICCAI 2018).

General Classification Lesion Segmentation

Data, Depth, and Design: Learning Reliable Models for Skin Lesion Analysis

1 code implementation1 Nov 2017 Eduardo Valle, Michel Fornaciali, Afonso Menegola, Julia Tavares, Flávia Vasques Bittencourt, Lin Tzy Li, Sandra Avila

We use the exhaustive trials to simulate sequential decisions and ensembles, with and without the use of privileged information from the test set.

Data Augmentation Transfer Learning

Knowledge Transfer for Melanoma Screening with Deep Learning

2 code implementations22 Mar 2017 Afonso Menegola, Michel Fornaciali, Ramon Pires, Flávia Vasques Bittencourt, Sandra Avila, Eduardo Valle

Knowledge transfer impacts the performance of deep learning -- the state of the art for image classification tasks, including automated melanoma screening.

Image Classification Skin Cancer Classification +1

RECOD Titans at ISIC Challenge 2017

4 code implementations14 Mar 2017 Afonso Menegola, Julia Tavares, Michel Fornaciali, Lin Tzy Li, Sandra Avila, Eduardo Valle

This extended abstract describes the participation of RECOD Titans in parts 1 and 3 of the ISIC Challenge 2017 "Skin Lesion Analysis Towards Melanoma Detection" (ISBI 2017).

General Classification Lesion Segmentation +1

Towards Automated Melanoma Screening: Proper Computer Vision & Reliable Results

2 code implementations14 Apr 2016 Michel Fornaciali, Micael Carvalho, Flávia Vasques Bittencourt, Sandra Avila, Eduardo Valle

In this paper we survey, analyze and criticize current art on automated melanoma screening, reimplementing a baseline technique, and proposing two novel ones.

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