Matches in SemOpenAlex for { <https://semopenalex.org/work/W4283390956> ?p ?o ?g. }
Showing items 1 to 73 of
73
with 100 items per page.
- W4283390956 endingPage "105629" @default.
- W4283390956 startingPage "105629" @default.
- W4283390956 abstract "Rock art is globally recognized as significant, yet the resources allocated to the study and exploration of this important form of cultural heritage are often scarce. In areas where numerous rock art sites exist, much of the rock art is unidentified and therefore remains, unrecorded and unresearched. Manually identifying rock art is time-consuming, tedious, and expensive. Therefore, it is necessary to automate many processes in rock art research, which can be accomplished by Machine Learning. Artificial Intelligence (AI) and Machine Learning (ML) can greatly facilitate rock art research in many ways, such as through Object Recognition and Detection, Motif Extraction, Object Reconstruction, Image Knowledge Graphs, and Representations. This article is a reflective work on the future of ML for rock art research. As a proof-of-concept, it presents a machine learning method based on recent advances in deep learning to train a model to identify images with painted rock art (pictograms). The efficacy of the proposed method is shown using data collected from fieldwork in Australia. Furthermore, our proposed method can be used to train models that are specific to the rock art found in different regions. We provide the code and the trained models in the supplementary section." @default.
- W4283390956 created "2022-06-25" @default.
- W4283390956 creator A5009322683 @default.
- W4283390956 creator A5042955373 @default.
- W4283390956 creator A5063772764 @default.
- W4283390956 date "2022-08-01" @default.
- W4283390956 modified "2023-10-17" @default.
- W4283390956 title "On the use of Machine Learning methods in rock art research with application to automatic painted rock art identification" @default.
- W4283390956 cites W2038233086 @default.
- W4283390956 cites W2053043445 @default.
- W4283390956 cites W2097117768 @default.
- W4283390956 cites W2522528007 @default.
- W4283390956 cites W2730890899 @default.
- W4283390956 cites W2738625345 @default.
- W4283390956 cites W2795718973 @default.
- W4283390956 cites W2897303157 @default.
- W4283390956 cites W2900891442 @default.
- W4283390956 cites W2925480424 @default.
- W4283390956 cites W2944334352 @default.
- W4283390956 cites W2962756421 @default.
- W4283390956 cites W2969502539 @default.
- W4283390956 cites W2986539979 @default.
- W4283390956 cites W2997010534 @default.
- W4283390956 cites W2999475299 @default.
- W4283390956 cites W3020655686 @default.
- W4283390956 cites W3036966662 @default.
- W4283390956 cites W3090770466 @default.
- W4283390956 cites W3122059549 @default.
- W4283390956 cites W3142448396 @default.
- W4283390956 cites W3192447662 @default.
- W4283390956 doi "https://doi.org/10.1016/j.jas.2022.105629" @default.
- W4283390956 hasPublicationYear "2022" @default.
- W4283390956 type Work @default.
- W4283390956 citedByCount "2" @default.
- W4283390956 countsByYear W42833909562023 @default.
- W4283390956 crossrefType "journal-article" @default.
- W4283390956 hasAuthorship W4283390956A5009322683 @default.
- W4283390956 hasAuthorship W4283390956A5042955373 @default.
- W4283390956 hasAuthorship W4283390956A5063772764 @default.
- W4283390956 hasConcept C116834253 @default.
- W4283390956 hasConcept C127313418 @default.
- W4283390956 hasConcept C166957645 @default.
- W4283390956 hasConcept C2776381685 @default.
- W4283390956 hasConcept C59822182 @default.
- W4283390956 hasConcept C86803240 @default.
- W4283390956 hasConcept C95457728 @default.
- W4283390956 hasConceptScore W4283390956C116834253 @default.
- W4283390956 hasConceptScore W4283390956C127313418 @default.
- W4283390956 hasConceptScore W4283390956C166957645 @default.
- W4283390956 hasConceptScore W4283390956C2776381685 @default.
- W4283390956 hasConceptScore W4283390956C59822182 @default.
- W4283390956 hasConceptScore W4283390956C86803240 @default.
- W4283390956 hasConceptScore W4283390956C95457728 @default.
- W4283390956 hasFunder F4320334704 @default.
- W4283390956 hasLocation W42833909561 @default.
- W4283390956 hasOpenAccess W4283390956 @default.
- W4283390956 hasPrimaryLocation W42833909561 @default.
- W4283390956 hasRelatedWork W1532644983 @default.
- W4283390956 hasRelatedWork W1548551537 @default.
- W4283390956 hasRelatedWork W1564980185 @default.
- W4283390956 hasRelatedWork W1924395272 @default.
- W4283390956 hasRelatedWork W2013910814 @default.
- W4283390956 hasRelatedWork W2087427185 @default.
- W4283390956 hasRelatedWork W2249991199 @default.
- W4283390956 hasRelatedWork W2810829458 @default.
- W4283390956 hasRelatedWork W3201629653 @default.
- W4283390956 hasRelatedWork W833609803 @default.
- W4283390956 hasVolume "144" @default.
- W4283390956 isParatext "false" @default.
- W4283390956 isRetracted "false" @default.
- W4283390956 workType "article" @default.