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- New dissimilarity measures for image phylogeny reconstruction
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Monthly Archives: April 2017
Our research about pornography detection on the News
Our research about pornography detection, recently published at Neurocomputing, is getting the attention of many News agencies in Brazil. It’s a good indicator to measure the great impact it has into our modern society. All of them are listed below … Continue reading
Posted in blog, extra, media
Tagged Deep learning, Neurocomputing, news, Pornography detection
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Talk: Multimedia Integrity Analytics
Today Prof. Anderson Rocha will give a talk at University of Kentucky about Multimedia Integrity Analytics. The talk is part of the university weekly seminars and presentation. Abstract: Currently, multimedia objects can be easily created, stored, (re)-transmitted, and edited for … Continue reading
Posted in blog, Keynotes, science, talk
Tagged Anderson Rocha, Multimedia Integrity Analytics, Multimedia Phylogeny, University of Kentucky
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Empirical Evaluation of Resampling Procedures for Optimising SVM Hyperparameters
Tuning the regularisation and kernel hyperparameters is a vital step in optimising the generalisation performance of kernel methods, such as the support vector machine (SVM). This is most often performed by minimising a resampling/cross-validation based model selection criterion, however there … Continue reading
RECOD’s Diabetic Retinopathy research on the news
Our research on Diabetic Retinopathy has gotten the attention of a well known website about health and wellness in Brazil. The article (in Portuguese) highlights the importance of diabetic retinopathy treatment and how the society can take advantage of our … Continue reading
Posted in blog, extra, media
Tagged Abril, Anderson Rocha, Diabetic Retinopathy, news, Ramon Pires, Saúde
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Empirical comparison of cross-validation and internal metrics for tuning SVM hyperparameters
Hyperparameter tuning is a mandatory step for building a support vector machine classifier. In this article, the authors study some methods based on metrics of the training set itself, and not the performance of the classifier on a different test … Continue reading
