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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Câmara, A., de Almeida, A., Caçador, D. & Oliveira, J. (2023). Automated methods for image detection of cultural heritage: Overviews and perspectives. Archaeological Prospection. 30 (2), 153-169
Exportar Referência (IEEE)
A. Câmara et al.,  "Automated methods for image detection of cultural heritage: Overviews and perspectives", in Archaeological Prospection, vol. 30, no. 2, pp. 153-169, 2023
Exportar BibTeX
@article{câmara2023_1731903373368,
	author = "Câmara, A. and de Almeida, A. and Caçador, D. and Oliveira, J.",
	title = "Automated methods for image detection of cultural heritage: Overviews and perspectives",
	journal = "Archaeological Prospection",
	year = "2023",
	volume = "30",
	number = "2",
	doi = "10.1002/arp.1883",
	pages = "153-169",
	url = "https://onlinelibrary.wiley.com/doi/10.1002/arp.1883"
}
Exportar RIS
TY  - JOUR
TI  - Automated methods for image detection of cultural heritage: Overviews and perspectives
T2  - Archaeological Prospection
VL  - 30
IS  - 2
AU  - Câmara, A.
AU  - de Almeida, A.
AU  - Caçador, D.
AU  - Oliveira, J.
PY  - 2023
SP  - 153-169
SN  - 1075-2196
DO  - 10.1002/arp.1883
UR  - https://onlinelibrary.wiley.com/doi/10.1002/arp.1883
AB  - Remote sensing data covering large geographical areas can be easily accessed and are being acquired with greater frequency. The massive volume of data requires an automated image analysis system. By taking advantage of the increasing availability of data using computer vision, we can design specific systems to automate data analysis and detection of archaeological objects. In the past decade, there has been a rise in the use of automated methods to assist in the identification of archaeological sites in remote sensing imagery. These applications offer an important contribution to non-intrusive archaeological exploration, helping to reduce the traditional human workload and time by signalling areas with a higher probability of presenting archaeological sites for exploration. This survey describes the state of the art of existing automated image analysis methods in archaeology and highlights the improvements thus achieved in the detection of archaeological monuments and areas of interest in landscape-scale satellite and aerial imagery. It also presents a discussion of the benefits and limitations of automatic detection of archaeological structures, proposing new approaches and possibilities.
ER  -