Please note: The algorithm descriptions in English have been automatically translated. Errors may have been introduced in this process. For the original descriptions, go to the Dutch version of the Algorithm Register.
Document search
- Publication category
- Other algorithms
- Impact assessment
- DPIA
- Status
- In use
General information
Theme
Begin date
Contact information
Link to publication website
Responsible use
Goal and impact
The purpose of the algorithms is to process source documents faster. The document recognition function categorises source documents. This determines whether a source document is on a list drawn up by a document expert. This is a list of documents that are not investigated further due to low risk of fraud. The "detail recognition" function helps to find features of authenticity on source documents.
Considerations
Document experts face a very high workload and limited capacity. The algorithms used help document experts deal efficiently with source documents with a low risk profile.
Human intervention
The document recognition algorithm learns from how document experts categorise scanned source documents. The algorithm's categorisation is always checked manually.
Risk management
Document experts check the results of the document recognition algorithm. They assess whether the source document has been recognised correctly. If the algorithm has given an incorrect result, the document experts correct it manually. Source documents with a low risk profile are also examined manually at random. The document experts are always responsible for the final recommendation. Detail recognition is only carried out manually by document experts. The results of this algorithm are supportive and are not automatically used in further document examination.
Legal basis
- Articles 14, 20, 28 and 45a of the Aliens Act stipulate that the Minister is authorised to grant, amend and/or revoke residence permits.
- Article 3:2 of the General Administrative Law Act stipulates that when preparing a decision, the administrative body must gather the necessary knowledge regarding the relevant facts and interests to be weighed up. An obligation to conduct an investigation, therefore.
Links to legal bases
- Article 14 Aliens Act: https://wetten.overheid.nl/jci1.3:c:BWBR0011823&hoofdstuk=3&afdeling=3¶graaf=1&artikel=14&z=2024-01-01&g=2024-01-01
- Article 20 Aliens Act: https://wetten.overheid.nl/jci1.3:c:BWBR0011823&hoofdstuk=3&afdeling=3¶graaf=2&artikel=20&z=2024-01-01&g=2024-01-01
- Article 28 Aliens Act: https://wetten.overheid.nl/jci1.3:c:BWBR0011823&hoofdstuk=3&afdeling=4¶graaf=1&artikel=28&z=2024-01-01&g=2024-01-01
- Section 45a Aliens Act: https://wetten.overheid.nl/jci1.3:c:BWBR0011823&hoofdstuk=3&afdeling=5¶graaf=1&artikel=45a&z=2024-01-01&g=2024-01-01
- - Article 3:2 General Administrative Law Act: https://wetten.overheid.nl/jci1.3:c:BWBR0005537&hoofdstuk=3&afdeling=3.2&artikel=3:2&z=2024-05-01&g=2024-05-01
Elaboration on impact assessments
DPIA has been carried out
Impact assessment
Operations
Data
High-quality digital scans of source documents and human annotations, such as country, document type and location of authenticity features. Document experts review the algorithms' predictions and create new annotations. After checking these annotations, they are added to the dataset used by the algorithms. Thus, the algorithms continue to learn about patterns in the data based on feedback from the document experts.
Technical design
For the document recognition algorithm, a VGG16 neural network was trained on characteristics of document data based on source document data. This allows, for example, to recognise the document type. The detail recognition algorithm uses a combination of existing visual models and neural networks trained internally on authenticity characteristics.
The source documents are scanned and presented to the system. The scan is also presented to the document recognition algorithm. The predicted categorisation is then checked by a document expert before the source document continues in the document search. During this document search, authenticity characteristics can be manually retrieved using the detail recognition algorithm.
External provider
Similar algorithm descriptions
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