Scene Detection in De Boer Historical Photo Collection
| Authors | |
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| Publication date | 2021 |
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| Book title | ICAART 2021 : Proceedings of the 13th International Conference on Agents and Artificial Intelligence : February 4-6, 2021. - Volume 1 |
| Book subtitle | ARTIDIGH 2021, Vienna, Austria |
| ISBN |
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| Event | Special Session on Artificial Intelligence and Digital Heritage |
| Pages (from-to) | 601-610 |
| Number of pages | 10 |
| Publisher | Setúbal: SciTePress |
| Organisations |
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| Abstract | This paper demonstrates how transfer learning can be used to improve scene detection applied to a historical press photo collection. After applying transfer learning to a pre-trained Places-365 ResNet-50 model, we achieve a Top-1 accuracy of .68 and a Top-5 accuracy of .89 on our data set, which consists of 132 categories. In addition to describing our annotation and training strategy, we also reflect on the use of transfer learning and the evaluation of computer vision models for heritage institutes. |
| Document type | Conference contribution |
| Language | English |
| Related dataset | Fotopersbureau De Boer Training Set on Scene Detection HisVis: Scene Detection Pilot Training Set Fotopersbureau De Boer Training Set on Scene Detection |
| Published at | https://doi.org/10.5220/0010288206010610 |
| Downloads |
ARTIDIGH_2021_1
(Final published version)
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