O uso da Divergência de Kullback-Leibler e da Divergência Generalizada como medida de similaridade em sistemas CBIR

The content-based image retrieval is important for various purposes like disease diagnoses from computerized tomography, for example. The relevance, social and economic of image retrieval systems has created the necessity of its improvement. Within this context, the content-based image retrieval systems are composed of two stages, the feature extraction and similarity measurement. The stage of similarity is still a challenge due to the wide variety of similarity measurement functions, which can be combined with the different techniques present in the recovery process and return results that aren’t always the most satisfactory. The most common functions used to measure the similarity are the Euclidean and Cosine, but some researchers have noted some limitations in these functions conventional proximity, in the step of search by similarity. For that reason, the Bregman divergences (Kullback Leibler and I-Generalized) have attracted the attention of researchers, due to its flexibility in the similarity analysis. Thus, the aim of this research was to conduct a comparative study over the use of Bregman divergences in relation the Euclidean and Cosine functions, in the step similarity of content-based image retrieval, checking the advantages and disadvantages of each function. For this, it was created a content-based image retrieval system in two stages: offline and online, using approaches BSM, FISM, BoVW and BoVW-SPM. With this system was created three groups of experiments using databases: Caltech101, Oxford and UK-bench. The performance of content-based image retrieval system using the different functions of similarity was tested through of evaluation measures: Mean Average Precision, normalized Discounted Cumulative Gain, precision at k, precision x recall. Finally, this study shows that the use of Bregman divergences (Kullback Leibler and Generalized) obtains better results than the Euclidean and Cosine measures with significant gains for content-based image retrieval.

O programa institucional de bolsa de iniciação à docência PIBID na formação inicial de professores de matemática

This research sought to understand the space training provided by Institutional Scholarship Program Initiation of Teaching to a group of students of Degree in Mathematics that had activities developed in the same public school. The goal is to qualify them for teaching practice for these basic institutions. We decided to conduct a qualitative study of type ethnographic case study. For a year and a half while we were at the meetings and activities of the Group, we did what we call as a participant observation. To obtain the data, we used different survey instruments: the researcher\'s field notes through his observation of everyday life of the group, photographs and filming of the activities, document analysis and database produced, physically and digitally, in addition to questionnaires and interviews with records written, which complemented each other and helped establish a triangulation of information collected. We analyze the trajectory of the group on three axes: on the first, we present and understand the paths taken by the Group in the process of setting up training spaces, and production of their professional training, in the second, we analyze how the space of PIBID is being integrated with others spaces of formations in the educational institution of the degree course in mathematics and, in the third axis, we understand the process of knowledge production of that group. The trajectory taken by the group was marked by a process of reflection and discussion systematic and collective, which favored the pursuit for be a better professional and also confirmed a possible path to be followed in initial teacher education.