task_categories:image-classification task_categories:image-segmentation language:en language:vi license:cc-by-nc-nd-4.0 code finance legal region:us
Data generation in machine learning involves creating or manipulating data to train
and evaluate machine learning models. The purpose of data generation is to provide
diverse and representative examples that cover a wide range of scenarios, ensuring the
model's robustness and generalization.
The dataset contains GENERATED Vietnamese passports, which are replicas of official
passports but with randomly generated details, such as name, date of birth etc.
The primary intention of generating these fake passports is to demonstrate the
structure and content of a typical passport document and to train the neural network to
identify this type of document.
Generated passports can assist in conducting research without accessing or compromising
real user data that is often sensitive and subject to privacy regulations. Synthetic
data generation allows researchers to *develop and refine models using simulated
passport data without risking privacy leaks*.
@InProceedings{huggingface:dataset,
title = {generated-vietnamese-passeports-dataset},
author = {TrainingDataPro},
year = {2023}
}
---
language:
- en
- vi
license: cc-by-nc-nd-4.0
task_categories:
- image-classification
- image-segmentation
tags:
- code
- finance
- legal
dataset_info:
  features:
  - name: id
    dtype: int32
  - name: image
    dtype: image
  splits:
  - name: train
    num_bytes: 28732495
    num_examples: 20
  download_size: 28741938
  dataset_size: 28732495
---

# GENERATED Vietnamese Passports Dataset
**Data generation** in machine learning involves creating or manipulating data to train and evaluate machine learning models. The purpose of data generation is to provide diverse and representative examples that cover a wide range of scenarios, ensuring the model's *robustness and generalization*.

The dataset contains GENERATED Vietnamese passports, which are replicas of official passports but with randomly generated details, such as *name, date of birth etc*. The primary intention of generating these fake passports is to demonstrate the structure and content of a typical passport document and to train the neural network to identify this type of document.

Generated passports can assist in conducting research without accessing or compromising real user data that is often sensitive and subject to privacy regulations. Synthetic data generation allows researchers to *develop and refine models using simulated passport data without risking privacy leaks*.

![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Ff2778d432611db436f18b9284daec240%2F666.png?generation=1691945421899877&alt=media)

### The dataset is solely for informational or educational purposes and should not be used for any fraudulent or deceptive activities.

# Get the dataset

### This is just an example of the data

Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=generated-vietnamese-passeports-dataset) to discuss your requirements, learn about the price and buy the dataset.

# Passports might be generated in accordance with your requirements.

## [**TrainingData**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=generated-vietnamese-passeports-dataset) provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets**

TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**