Formal concept analysis with negative attributes for forgery detection

 

Abstract

Citation

Please, cite this work as:

[OR21] M. Ojeda-Aciego and J. M. Rodr'-Jiménez. “Formal concept analysis with negative attributes for forgery detection”. In: Comput. Math. Methods 3.6 (2021). DOI: 10.1002/CMM4.1124. URL: https://doi.org/10.1002/cmm4.1124.

NoteBibTeX

@Article{OjedaAciego2021,
     author = {Manuel Ojeda-Aciego and Jos{’e} Manuel Rodr'-Jim{’e}nez},
     journal = {Comput. Math. Methods},
     title = {Formal concept analysis with negative attributes for forgery detection},
     year = {2021},
     number = {6},
     volume = {3},
     bibsource = {dblp computer science bibliography, https://dblp.org},
     biburl = {https://dblp.org/rec/journals/cmm/OjedaAciegoR21.bib},
     doi = {10.1002/CMM4.1124},
     timestamp = {Tue, 31 Jan 2023 00:00:00 +0100},
     url = {https://doi.org/10.1002/cmm4.1124},
}

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Formal concept analysis with negative attributes for forgery detection

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Papers citing this work

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

[1] C. Devlin, M. Morelato, and S. Baechler. “Forensic intelligence: Expanding the potential of forensic document examination”. In: WIREs Forensic Science 6.5 (Jul. 2024). ISSN: 2573-9468. DOI: 10.1002/wfs2.1528. URL: http://dx.doi.org/10.1002/wfs2.1528.

[2] M. Ojeda-Aciego and J. M. Rodríguez-Jiménez. “Advances in Forgery Detection of Driving Licences Using Truthfulness Degrees”. In: Computational Intelligence and Mathematics for Tackling Complex Problems 4. Springer International Publishing, Sep. 2022, p. 145–151. ISBN: 9783031077074. DOI: 10.1007/978-3-031-07707-4_18. URL: http://dx.doi.org/10.1007/978-3-031-07707-4_18.

[3] J. M. Rodríguez Jiménez, M. Á. Canorea Ruiz, and A. Plaza Quesada. “Detección de alteración de motores ubicados en motocicletas”. In: Ciencia Policial 183 (Dec. 2024), p. 15–41. ISSN: 2254-0326. DOI: 10.14201/cp.32162. URL: http://dx.doi.org/10.14201/cp.32162.

[4] P. Sokol, Ľ. Antoni, O. Krídlo, et al. “Formal concept analysis approach to understand digital evidence relationships”. In: International Journal of Approximate Reasoning 159 (Aug. 2023), p. 108940. ISSN: 0888-613X. DOI: 10.1016/j.ijar.2023.108940. URL: http://dx.doi.org/10.1016/j.ijar.2023.108940.