Growing Competitive Network for Tracking Objects in Video Sequences

Neural networks

Image processing

Authors

Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael Marcos Luque Baena, Domingo López-Rodríguez, Esteban J. Palomo

Published

27 April 2009

Publication details

International Conference on Adaptive and Natural Computing Algorithms 2009, pp 109 – 118

Links

Abstract

In this paper, we investigate the use of artificial neural networks in order to solve the Shortest Common Superstring Problem. Concretely, the neural network used in this work is based on a multivalued model, MREM, very suitable for solving combinatorial optimization problems. We describe the foundations of this neural model, and how it can be implemented in the context of this problem, by taking advantage of a better representation than in other models, which, in turn, contributes to ease the computational dynamics of the model. Experimental results prove that our model outperforms other heuristic approaches known from the specialized literature.

Citation

Please, cite this work as:

[Ort+09] J. M. Ortiz-de-Lazcano-Lobato, R. M. Luque, D. López-Rodríguez, et al. “Growing Competitive Network for Tracking Objects in Video Sequences”. In: Adaptive and Natural Computing Algorithms, 9th International Conference, ICANNGA 2009, Kuopio, Finland, April 23-25, 2009, Revised Selected Papers. Ed. by M. Kolehmainen, P. J. Toivanen and B. Beliczynski. Vol. 5495. Lecture Notes in Computer Science. Springer, 2009, pp. 109-118. DOI: 10.1007/978-3-642-04921-7_12. URL: https://doi.org/10.1007/978-3-642-04921-7_12.

BibTeX

@inproceedings{OLLP09,
     author = {Juan Miguel Ortiz{-}de{-}Lazcano{-}Lobato and Rafael Marcos Luque and Domingo López{-}Rodríguez and Esteban J. Palomo},
     editor = {Mikko Kolehmainen and Pekka J. Toivanen and Bartlomiej Beliczynski},
     title = {Growing Competitive Network for Tracking Objects in Video Sequences},
     booktitle = {Adaptive and Natural Computing Algorithms, 9th International Conference, {ICANNGA} 2009, Kuopio, Finland, April 23-25, 2009, Revised Selected Papers},
     series = {Lecture Notes in Computer Science},
     volume = {5495},
     pages = {109–118},
     publisher = {Springer},
     year = {2009},
     url = {https://doi.org/10.1007/978-3-642-04921-7_12},
     doi = {10.1007/978-3-642-04921-7_12}
}

Bibliometric data

The following data has been extracted from resources such as OpenAlex, Dimensions, PlumX or Altmetric.

Citations
Scopus - Citation Indexes: 1

Captures
Mendeley - Readers: 7

Cites

The following graph plots the number of cites received by this work from its publication, on a yearly basis.

Papers citing this work

The following is a non-exhaustive list of papers that cite this work:

[1] M. Kaushal, B. S. Khehra, and A. Sharma. “Soft Computing based object detection and tracking approaches: State-of-the-Art survey”. In: Applied Soft Computing 70 (Sep. 2018), p. 423–464. ISSN: 1568-4946. DOI: 10.1016/j.asoc.2018.05.023. URL: http://dx.doi.org/10.1016/j.asoc.2018.05.023.