2016
DOI: 10.1007/s00138-016-0819-x
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Image-based search and retrieval for biface artefacts using features capturing archaeologically significant characteristics

Abstract: Archaeologists are currently producing huge numbers of digitized photographs to record and preserve artefact finds. These images are used to identify and categorize artefacts and reason about connections between artefacts and perform outreach to the public. However, finding specific types of images within collections remains a major challenge. Often, the metadata associated with images is sparse or is inconsistent. This makes keyword-based exploratory search difficult, leaving researchers to rely on serendipit… Show more

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Cited by 5 publications
(2 citation statements)
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References 24 publications
(27 reference statements)
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“…A further challenge to understanding user experience and information needs online comes from the variable quality of digital objects and collections themselves. Most of the time the metadata associated with cultural objects, such as images, is either sparse or inconsistent, and this makes keyword-based exploratory search difficult and therefore slows down the research or engagement process [17]. User modelling can describe the interaction process between users and cultural heritage applications and products [18]; however, despite a myriad of research reported over the past two decades or so, there is a lack of a richer and deeper understanding of digital users [19].…”
Section: Introductionmentioning
confidence: 99%
“…A further challenge to understanding user experience and information needs online comes from the variable quality of digital objects and collections themselves. Most of the time the metadata associated with cultural objects, such as images, is either sparse or inconsistent, and this makes keyword-based exploratory search difficult and therefore slows down the research or engagement process [17]. User modelling can describe the interaction process between users and cultural heritage applications and products [18]; however, despite a myriad of research reported over the past two decades or so, there is a lack of a richer and deeper understanding of digital users [19].…”
Section: Introductionmentioning
confidence: 99%
“…) in digital libraries that otherwise would require a highly laborious annotation process by trained and skilled users (Canul-Ku et al, 2018;Engel et al, 2019;Dhali et al, 2020). In the case of image-based datasets, computer vision methods have been used to analyse and annotate photos e.g., the geo-reference of series of aerial photos (Cantoro, 2014), the semantic analysis of a digital library of museum artefacts, or a collection of old photographs for the semantic categorisation of contents (Eramian et al, 2017).…”
Section: Introductionmentioning
confidence: 99%