Analyzing the potential of active learning for document image classification
CC BY
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| Định dạng: | Sách |
| Ngôn ngữ: | English |
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Springer
2023
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| Truy cập trực tuyến: | https://link.springer.com/article/10.1007/s10032-023-00429-8 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8348 |
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oai:localhost:PNK-83482023-04-27T02:01:06Z Analyzing the potential of active learning for document image classification Saifullah, Saifullah Stefan, Agne Andreas, Dengel potential of active learning CC BY Deep learning has been extensively researched in the field of document analysis and has shown excellent performance across a wide range of document-related tasks. As a result, a great deal of emphasis is now being placed on its practical deployment and integration into modern industrial document processing pipelines. It is well known, however, that deep learning models are data-hungry and often require huge volumes of annotated data in order to achieve competitive performances. And since data annotation is a costly and labor-intensive process, it remains one of the major hurdles to their practical deployment. This study investigates the possibility of using active learning to reduce the costs of data annotation in the context of document image classification, which is one of the core components of modern document processing pipelines. 2023-04-27T02:01:06Z 2023-04-27T02:01:06Z 2023 Book https://link.springer.com/article/10.1007/s10032-023-00429-8 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8348 en application/pdf Springer |
| institution |
Digital Phenikaa |
| collection |
Digital Phenikaa |
| language |
English |
| topic |
potential of active learning |
| spellingShingle |
potential of active learning Saifullah, Saifullah Stefan, Agne Andreas, Dengel Analyzing the potential of active learning for document image classification |
| description |
CC BY |
| format |
Book |
| author |
Saifullah, Saifullah Stefan, Agne Andreas, Dengel |
| author_facet |
Saifullah, Saifullah Stefan, Agne Andreas, Dengel |
| author_sort |
Saifullah, Saifullah |
| title |
Analyzing the potential of active learning for document image classification |
| title_short |
Analyzing the potential of active learning for document image classification |
| title_full |
Analyzing the potential of active learning for document image classification |
| title_fullStr |
Analyzing the potential of active learning for document image classification |
| title_full_unstemmed |
Analyzing the potential of active learning for document image classification |
| title_sort |
analyzing the potential of active learning for document image classification |
| publisher |
Springer |
| publishDate |
2023 |
| url |
https://link.springer.com/article/10.1007/s10032-023-00429-8 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8348 |
| _version_ |
1764358630545555456 |
| score |
8.881002 |