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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2512.19958 |
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| _version_ | 1866909974461939712 |
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| author | Oommen, Sneha Sanchez, Gabby Britto, Cassandra T. Wang, Di Chiou, Jordan Spichkova, Maria |
| author_facet | Oommen, Sneha Sanchez, Gabby Britto, Cassandra T. Wang, Di Chiou, Jordan Spichkova, Maria |
| contents | This paper presents an evaluation of the AWS Textract in the context of extracting data from receipts. We analyse Textract functionalities using a dataset that includes receipts of varied formats and conditions. Our analysis provided a qualitative view of Textract strengths and limitations. While the receipts totals were consistently detected, we also observed typical issues and irregularities that were often influenced by image quality and layout. Based on the analysis of the observations, we propose mitigation strategies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_19958 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Towards Analysing Invoices and Receipts with Amazon Textract Oommen, Sneha Sanchez, Gabby Britto, Cassandra T. Wang, Di Chiou, Jordan Spichkova, Maria Information Retrieval Software Engineering This paper presents an evaluation of the AWS Textract in the context of extracting data from receipts. We analyse Textract functionalities using a dataset that includes receipts of varied formats and conditions. Our analysis provided a qualitative view of Textract strengths and limitations. While the receipts totals were consistently detected, we also observed typical issues and irregularities that were often influenced by image quality and layout. Based on the analysis of the observations, we propose mitigation strategies. |
| title | Towards Analysing Invoices and Receipts with Amazon Textract |
| topic | Information Retrieval Software Engineering |
| url | https://arxiv.org/abs/2512.19958 |