Search Results - "Traina, Caetano"

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  1. 1

    Approximate XML structure validation based on document–grammar tree similarity by Tekli, Joe, Chbeir, Richard, Traina, Agma J.M., Traina, Caetano, Fileto, Renato

    Published in Information sciences (20-02-2015)
    “…Comparing XML documents with XML grammars, also known as XML document and grammar validation, is useful in various applications such as: XML document…”
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    Journal Article
  2. 2

    Querying on large and complex databases by content: Challenges on variety and veracity regarding real applications by Traina, Agma J.M., Brinis, Safia, Pedrosa, Glauco V., Avalhais, Letricia P.S., Traina, Caetano

    Published in Information systems (Oxford) (01-12-2019)
    “…The amount and variety of digital data currently being generated, stored and analyzed, including images, videos, and time series, have brought challenges to…”
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    Journal Article
  3. 3

    How to speed up outliers removal in image matching by Ramos, Jonathan S., Watanabe, Carolina Y.V., Traina, Caetano, Traina, Agma J.M.

    Published in Pattern recognition letters (15-10-2018)
    “…•A preprocessing technique to speed up the outliers removal from matched point is proposed.•Almost all inliers are kept while a high portion of the outliers…”
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    Journal Article
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    Segmenting skin ulcers and measuring the wound area using deep convolutional networks by Chino, Daniel Y.T., Scabora, Lucas C., Cazzolato, Mirela T., Jorge, Ana E.S., Traina-Jr, Caetano, Traina, Agma J.M.

    “…•Wound area measurement assists healthcare professionals in patients’ follow-up.•Convolutional neural networks accurately segment skin ulcer wounds.•The…”
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    Journal Article
  6. 6

    Smart histogram analysis applied to the skull-stripping problem in T1-weighted MRI by Balan, André G.R, Traina, Agma J.M, Ribeiro, Marcela X, Marques, Paulo M.A, Traina Jr., Caetano

    Published in Computers in biology and medicine (01-05-2012)
    “…Abstract In this paper we address the “skull-stripping” problem in 3D MR images. We propose a new method that employs an efficient and unique histogram…”
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    Journal Article
  7. 7

    ClinicalPath: A Visualization Tool to Improve the Evaluation of Electronic Health Records in Clinical Decision-Making by Linhares, Claudio D. G., Lima, Daniel M., Ponciano, Jean R., Olivatto, Mauro M., Gutierrez, Marco A., Poco, Jorge, Traina, Caetano, Traina, Agma J. M.

    “…Physicians work at a very tight schedule and need decision-making support tools to help on improving and doing their work in a timely and dependable manner…”
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    Journal Article
  8. 8

    A superpixel-driven deep learning approach for the analysis of dermatological wounds by Blanco, Gustavo, Traina, Agma J.M., Traina Jr, Caetano, Azevedo-Marques, Paulo M., Jorge, Ana E.S., de Oliveira, Daniel, Bedo, Marcos V.N.

    “…•A new proposal based on superpixels and deep-learning models for wound segmentation is proposed.•Distinct parameterizations for the approach are discussed and…”
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    Journal Article
  9. 9

    Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS by Tekli, Joe, Chbeir, Richard, Traina, Agma J.M., Traina, Caetano, Yetongnon, Kokou, Ibanez, Carlos Raymundo, Al Assad, Marc, Kallas, Christian

    Published in Data & knowledge engineering (01-09-2018)
    “…In the past decade, there has been an increasing need for semantic-aware data search and indexing in textual (structured and NoSQL) databases, as full-text…”
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    Journal Article
  10. 10

    PRoSPer: Perceptual similarity queries in medical CBIR systems through user profiles by Bugatti, Pedro H, Kaster, Daniel S, Ponciano-Silva, Marcelo, Traina, Caetano, Azevedo-Marques, Paulo M, Traina, Agma J.M

    Published in Computers in biology and medicine (01-02-2014)
    “…Abstract In this paper, we present a novel approach to perform similarity queries over medical images, maintaining the semantics of a given query posted by the…”
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    Journal Article
  11. 11

    The Omni-family of all-purpose access methods : a simple and effective way to make similarity search more efficient by TRAINA, Caetano, SANTOS, Roberto F, TRAINA, Agma J. M, VIEIRA, Marcos R, FALOUTSOS, Christos

    Published in The VLDB journal (01-10-2007)
    “…Similarity search operations require executing expensive algorithms, and although broadly useful in many new applications, they rely on specific structures not…”
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    Journal Article
  12. 12

    Open issues for partitioning clustering methods: an overview by Barioni, Maria Camila N., Razente, Humberto, Marcelino, Alessandra M. R., Traina, Agma J. M., Traina Jr, Caetano

    “…Over the last decades, a great variety of data mining techniques have been developed to reach goals concerning Knowledge Discovery in Databases. Among them,…”
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    Journal Article
  13. 13

    The UTrack framework for segmenting and measuring dermatological ulcers through telemedicine by Cazzolato, Mirela T., Ramos, Jonathan S., Rodrigues, Lucas S., Scabora, Lucas C., Chino, Daniel Y.T., Jorge, Ana E.S., de Azevedo-Marques, Paulo Mazzoncini, Traina, Caetano, Traina, Agma J.M.

    Published in Computers in biology and medicine (01-07-2021)
    “…Chronic dermatological ulcers cause great discomfort to patients, and while monitoring the size of wounds over time provides significant clues about the…”
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    Journal Article
  14. 14

    Improving the ranking quality of medical image retrieval using a genetic feature selection method by da Silva, Sérgio Francisco, Ribeiro, Marcela Xavier, Batista Neto, João do E.S., Traina-Jr, Caetano, Traina, Agma J.M.

    Published in Decision Support Systems (01-11-2011)
    “…In this paper, we take advantage of single-valued functions that evaluate rankings to develop a family of feature selection methods based on the genetic…”
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    Journal Article
  15. 15

    CLAP, ACIR and SCOOP: Novel techniques for improving the performance of dynamic Metric Access Methods by Oliveira, Paulo H., Traina Jr, Caetano, Kaster, Daniel S.

    Published in Information systems (Oxford) (01-12-2017)
    “…•Techniques for improving Metric Access Methods in similarity queries are proposed.•CLAP technique reduces the number of distance calculations.•ACIR and SCOOP…”
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    Journal Article
  16. 16

    The Merkurion approach for similarity searching optimization in Database Management Systems by Bedo, Marcos V.N., Kaster, Daniel S., Traina, Agma J.M., Traina Jr, Caetano

    Published in Data & knowledge engineering (01-01-2018)
    “…Modern Database Management Systems (DBMSs) retrieve songs that resemble those in a music dataset, identify plagiarism in a set of documents, or provide past…”
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    Journal Article
  17. 17

    Wia-Spine: A CBIR environment with embedded radiomic features to assess fragility fractures by Bedo, Marcos, Ramos, Jonathan S., Traina, Agma J. M., Traina, Caetano, Nogueira-Barbosa, Marcello H., Azevedo-Marques, Paulo M.

    “…Osteoporosis is a systemic disorder that reduces the bone mineral density, increasing the vertebrae's fragility and proneness to fracture. Although the bone…”
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    Conference Proceeding
  18. 18

    BREATH: Heat Maps Assisting the Detection of Abnormal Lung Regions in CT Scans by Cazzolato, Mirela T., Scabora, Lucas C., Costa, Alceu F., Nesso, Marcos R., Milano-Oliveira, Luis F., Kaster, Daniel S., Traina, Caetano, Traina, Agma J.M.

    “…Computed Tomography (CT) scans are often employed to diagnose lung diseases, as abnormal tissue regions may indicate whether proper treatment is required…”
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    Conference Proceeding
  19. 19

    Large Graph Analysis in the GMine System by Rodrigues, Jr, Jose F., Tong, Hanghang, Pan, Jia-Yu, Traina, Agma J.M., Traina, Jr, Caetano, Faloutsos, Christos

    “…Current applications have produced graphs on the order of hundreds of thousands of nodes and millions of edges. To take advantage of such graphs, one must be…”
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    Journal Article
  20. 20

    A fast and effective method to find correlations among attributes in databases by de Sousa, Elaine P. M., Traina, Caetano, Traina, Agma J. M., Wu, Leejay, Faloutsos, Christos

    Published in Data mining and knowledge discovery (01-06-2007)
    “…The problem of identifying meaningful patterns in a database lies at the very heart of data mining. A core objective of data mining processes is the…”
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    Journal Article