I'm currently working as a researcher in the Center for Geosciences Applied to Petroleum Geology (UNESPetro) under the partnership UNESP-Petrobras. I received my Bachelor's Degree in Computer Science from the São Paulo State University (UNESP) in 2016. I obtained my Master's Degree in Computer Science from the São Paulo State University (UNESP) in 2019 with the thesis ?Unsupervised Selective Rank Fusion for Content-based Image Retrieval.?. I have experience in different areas of Computer Science, with special interest in information retrieval, image retrieval by content, machine learning, computer vision, deep learning, image processing, pattern recognition, and parallel computing. My work "Unsupervised Similarity Learning through Cartesian Product of Ranking References for Image Retrieval Tasks" was awarded as Best Paper in the SIBGRAPI' 16 (Conference on Graphics, Patterns and Images). It was also recognized as the best undergraduate research of the São Paulo State University in 2016 and awarded as the best undergraduate work by the SBC (Brazilian Computer Society) in 2017. (Source: Lattes Curriculum)
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The evolution of the mobile devices and the consequent facilities in the processes of acquisition and sharing of visual content have caused a great growth in the collections of images. In this scenario, it becomes imperative to develop automatic methods that allow indexing, analyzing and searching in such content. Content-Based Image Retrieval (CBIR) are a promising solution. However, ass…
Content-Based Image Retrieval (CBIR) systems aims at retrieving the most similar images in a collection by taking into account image visual properties. Users are interested in the images placed at the first positions of the returned ranked lists, which usually are the most relevant ones. Therefore, accurately ranking collection images is of great relevance. However, in general, CBIR appro…
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