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Ana Paula B. Lopes

Researcher at Universidade Federal de Minas Gerais

Publications -  22
Citations -  1026

Ana Paula B. Lopes is an academic researcher from Universidade Federal de Minas Gerais. The author has contributed to research in topics: Feature extraction & Image retrieval. The author has an hindex of 8, co-authored 18 publications receiving 838 citations. Previous affiliations of Ana Paula B. Lopes include State University of Santa Cruz.

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VSUMM: A mechanism designed to produce static video summaries and a novel evaluation method

TL;DR: VSUMM is presented, a methodology for the production of static video summaries that is based on color feature extraction from video frames and k-means clustering algorithm and develops a novel approach for the evaluation of video static summaries.
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A bag-of-features approach based on Hue-SIFT descriptor for nude detection

TL;DR: This work uses an extension to the well-known SIFT descriptor - called Hue-SIFT - aimed at adding color information to the original SIFT, which shows recognition rates which are similar to those achieved by other approaches in literature.
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MammoSys: A content-based image retrieval system using breast density patterns

TL;DR: A content-based image retrieval system designed to retrieve mammographies from large medical image database based on breast density, and integrated to the database of the Image Retrieval in Medical Applications (IRMA) project, that provides images with classification ground truth.
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Three-Dimensional Stable Alginate-Nanocellulose Gels for Biomedical Applications: Towards Tunable Mechanical Properties and Cell Growing.

TL;DR: The morphological characteristics, the mechanical properties, and the non-cytotoxic behavior of the CNFT-alginate gels improved bioadhesion, growth, and proliferation of the cells onto the gels, which might find applications in tissue engineering field, as for instance, in tissue repair or wound healing applications.
Proceedings ArticleDOI

Nude Detection in Video Using Bag-of-Visual-Features

TL;DR: The results of the experiments show that this approach is indeed able to provide good recognition rates for nudity even at the frame level and with a relatively low sampling ratio, and the proposed voting scheme significantly enhances the recognition rate for video segments.