Zobrazeno 1 - 10
of 154
pro vyhledávání: '"Traina, A. J. M."'
Autor:
Tinarrage, Raphaël, Ponciano, Jean R., Linhares, Claudio D. G., Traina, Agma J. M., Poco, Jorge
Temporal graphs are commonly used to represent complex systems and track the evolution of their constituents over time. Visualizing these graphs is crucial as it allows one to quickly identify anomalies, trends, patterns, and other properties leading
Externí odkaz:
http://arxiv.org/abs/2304.03828
Autor:
Linhares, Claudio D. G., Ponciano, Jean R., Pedro, Diogenes S., Rocha, Luis E. C., Traina, Agma J. M., Poco, Jorge
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics, 2022
Temporal (or time-evolving) networks are commonly used to model complex systems and the evolution of their components throughout time. Although these networks can be analyzed by different means, visual analytics stands out as an effective way for a p
Externí odkaz:
http://arxiv.org/abs/2208.04358
Autor:
Linhares, Claudio D. G., Lima, Daniel M., Ponciano, Jean R., Olivatto, Mauro M., Gutierrez, Marco A., Poco, Jorge, Traina Jr., 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. Examining piles of sheets with test results and using systems with little visualization suppo
Externí odkaz:
http://arxiv.org/abs/2205.13570
Autor:
Blanco, Gustavo, Traina, Agma J. M., Traina Jr., Caetano, Azevedo-Marques, Paulo M., Jorge, Ana E. S., de Oliveira, Daniel, Bedo, Marcos V. N.
Background. The image-based identification of distinct tissues within dermatological wounds enhances patients' care since it requires no intrusive evaluations. This manuscript presents an approach, we named QTDU, that combines deep learning models wi
Externí odkaz:
http://arxiv.org/abs/1909.06264
Autor:
Ramos, Jonathan S., Cazzolato, Mirela T., Faiçal, Bruno S., Nogueira-Barbosa, Marcello H., Traina Jr., Caetano, Traina, Agma J. M.
Publikováno v:
Computer-Based Medical Systems, 2019
Segmentation of medical images is critical for making several processes of analysis and classification more reliable. With the growing number of people presenting back pain and related problems, the semi-automatic segmentation and 3D reconstruction o
Externí odkaz:
http://arxiv.org/abs/1906.10288
Autor:
Ramos, Jonathan S., Watanabe, Carolina Y. V., Nogueira-Barbosa, Marcello H., Traina, Agma J. M.
Publikováno v:
The 34th ACM/SIGAPP Symposium on Applied Computing (SAC2019)
Segmentation of medical images is a critical issue: several process of analysis and classification rely on this segmentation. With the growing number of people presenting back pain and problems related to it, the automatic or semi-automatic segmentat
Externí odkaz:
http://arxiv.org/abs/1906.08620
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Emergency events involving fire are potentially harmful, demanding a fast and precise decision making. The use of crowdsourcing image and videos on crisis management systems can aid in these situations by providing more information than verbal/textua
Externí odkaz:
http://arxiv.org/abs/1506.03495
Autor:
Rodrigues Jr., Jose F., Traina, Agma J. M., de Oliveira, Maria Cristina F., Traina Jr, Caetano
This paper presents an analytical taxonomy that can suitably describe, rather than simply classify, techniques for data presentation. Unlike previous works, we do not consider particular aspects of visualization techniques, but their mechanisms and f
Externí odkaz:
http://arxiv.org/abs/1506.02976
Publikováno v:
Information Visualization 6: 4. 261-279 (2007)
We revisit the design space of visualizations aiming at identifying and relating its components. In this sense, we establish a model to examine the process through which visualizations become expressive for users. This model has leaded us to a taxono
Externí odkaz:
http://arxiv.org/abs/1505.07804