Showing papers by "Daniel Rodriguez published in 2015"
30 Aug 2015
TL;DR: This work summarizes the main topics that have been researched in the area of software testing under the umbrella of ``Bayesian approaches'' since 2010 and selected around 40 references applying Bayesian approaches in the field of softwareTesting since 2010 to foster better focused research.
Abstract: This work summarizes the main topics that have been researched in the area of software testing under the umbrella of ``Bayesian approaches'' since 2010 There is a growing trend on the use of the so-called Bayesian statistics and Bayesian concepts in general and software testing in particular Following a Systematic Literature Review protocol using the main digital libraries and repositories, we selected around 40 references applying Bayesian approaches in the field of software testing since 2010 Those references summarise the current state of the art and foster better focused research So far, the main observed use of the Bayesian concepts in the software testing field is through the application of Bayesian networks for software reliability and defect prediction (the latter is mainly based on static software metrics and Bayesian classifiers) Other areas of application are software estimation and test data generation There are areas not fully explored beyond the basic Bayesian approaches, such as influence diagrams and dynamic networks
10 citations
TL;DR: This work proposes a biometric identification system that works together with a palm vein reader sensor and a hand-clenching support, designed to perform the capture the back of the hand.
Abstract: This work proposes a biometric identification system that works together with a palm vein reader sensor and a hand-clenching support, designed to perform the capture the back of the hand. Several processing steps were performed: extraction of the region of interest, binarization, dilation, noise filtering, skeletonization, as well as extraction and verification of patterns based on the measurment of coincidence of vertical and horizontal displacements of skeletonized and dilated images. The proposed method achieved the following results: processing time post capture of 1.8 seconds, FRR of 0.47% and FAR of 0,00%, with a referential database of 50 people from a total of 1500 random captures.
7 citations