7 datasets found
  1. P

    VSAI Dataset Dataset

    • paperswithcode.com
    Updated Mar 23, 2025
    + more versions
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    (2025). VSAI Dataset Dataset [Dataset]. https://paperswithcode.com/dataset/vsai-dataset
    Explore at:
    Dataset updated
    Mar 23, 2025
    Description

    Description:

    👉 Download the dataset here

    The VSAI (Vehicle Surveillance via Aerial Imagery) Dataset is a highly versatile and expansive collection of high-resolution aerial images gathered from multiple drone platforms. Covering a diverse geographical expanse, this dataset is specifically curated to support vehicle detection tasks in various complex real-world environments. It offers a multi-view perspective of different urban and rural areas, captured under a wide range of conditions.

    This unique dataset is designed for advancing object detection in aerial imagery by addressing numerous real-world challenges, such as varying camera angles, diverse flight altitudes, changing weather conditions, and fluctuating light intensities. VSAI captures imagery from different times of the day and seasons, making it an essential resource for building more robust vehicle detection models.

    Download Dataset

    Dataset Composition

    The VSAI dataset contains an impressive 49,712 vehicle instances meticulously annotated using oriented bounding boxes and arbitrary quadrilateral bounding boxes. This level of precision in annotation accommodates varying object shapes and positions in aerial views, enhancing the dataset's utility for training advanced object detection algorithms. It includes annotations for:

    Small Vehicles: 47,519 instances

    Large Vehicles: 2,193 instances

    To enhance model robustness, the dataset also includes detailed annotations of occlusion rates, helping algorithms generalize better under challenging scenarios like partial visibility caused by environmental factors or other objects.

    Key Features

    Diverse Capture Conditions: The images in VSAI are captured across multiple drone platforms, which vary in altitude, camera angles, and flight paths.

    Complex Scenarios: The dataset spans a wide range of environments, including urban centers, rural landscapes, industrial areas, and highways, representing real-world complexities.

    Varied Temporal and Weather Conditions: Images have been captured during different times of the day and under diverse weather conditions, including clear skies, overcast, rainy, and foggy environments.

    High Annotation Accuracy: Vehicle instances are annotated with highly precise bounding boxes, including both oriented and arbitrary quadrilateral shapes, to reflect the true contours of vehicles as seen from an aerial perspective.

    Occlusion Annotation: Objects in the dataset are also labeled with their occlusion levels, providing additional challenges for model training and improving detection performance in scenarios with partially visible vehicles.

    This dataset is sourced from Kaggle.

  2. Visual Anomaly (VisA)

    • registry.opendata.aws
    Updated Nov 9, 2022
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    Amazon Web Services (2022). Visual Anomaly (VisA) [Dataset]. https://registry.opendata.aws/visa/
    Explore at:
    Dataset updated
    Nov 9, 2022
    Dataset provided by
    Amazon Web Serviceshttp://aws.amazon.com/
    Amazon Web Serviceshttps://aws.amazon.com/
    Description

    Largest Visual Anomaly detection dataset containing objects from 12 classes in 3 domains across 10,821(9,621 normal and 1,200 anomaly) images. Both image and pixel level annotations are provided.

  3. VSAI_data

    • kaggle.com
    Updated May 3, 2025
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    babysree gangarapu (2025). VSAI_data [Dataset]. https://www.kaggle.com/datasets/babysreegangarapu/vsai-data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 3, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    babysree gangarapu
    Description

    Dataset

    This dataset was created by babysree gangarapu

    Contents

  4. h

    visa-dataset

    • huggingface.co
    Updated Dec 20, 2024
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    Drax (2024). visa-dataset [Dataset]. https://huggingface.co/datasets/dddraxxx/visa-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 20, 2024
    Authors
    Drax
    Description

    dddraxxx/visa-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

  5. t

    VSAI|Full export Customs Data Records|tradeindata

    • tradeindata.com
    Updated Mar 23, 2021
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    tradeindata (2021). VSAI|Full export Customs Data Records|tradeindata [Dataset]. https://www.tradeindata.com/supplier_detail/?id=31c1b6b379f835480230f65342fb4ef0
    Explore at:
    Dataset updated
    Mar 23, 2021
    Dataset authored and provided by
    tradeindata
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Customs records of Switzerland are available for VSAI. Learn about its Importer, supply capabilities and the countries to which it supplies goods

  6. h

    human-vs-Ai-generated-dataset

    • huggingface.co
    Updated May 29, 2025
    + more versions
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    ahmadreza anaami (2025). human-vs-Ai-generated-dataset [Dataset]. https://huggingface.co/datasets/ahmadreza13/human-vs-Ai-generated-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 29, 2025
    Authors
    ahmadreza anaami
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    ahmadreza13/human-vs-Ai-generated-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

  7. h

    ghibli-dataset

    • huggingface.co
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    WooHyeok, Choi, ghibli-dataset [Dataset]. https://huggingface.co/datasets/pulnip/ghibli-dataset
    Explore at:
    Authors
    WooHyeok, Choi
    License

    https://choosealicense.com/licenses/other/https://choosealicense.com/licenses/other/

    Description

    Ghibli Real vs AI-Generated Dataset

    One sample per line

    Includes: id, image, label, description

    Use this for standard classification or image-text training

    Real images sourced from Nechintosh/ghibli (810 images)

    AI-generated images created using:

    nitrosocke/Ghibli-Diffusion (2637 images) KappaNeuro/studio-ghibli-style (810 images) Note: While the KappaNeuro repository does not explicitly state a license, it is a fine-tuned model based on Stable Diffusion XL, which is… See the full description on the dataset page: https://huggingface.co/datasets/pulnip/ghibli-dataset.

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Share
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Click to copy link
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Close
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(2025). VSAI Dataset Dataset [Dataset]. https://paperswithcode.com/dataset/vsai-dataset

VSAI Dataset Dataset

Explore at:
Dataset updated
Mar 23, 2025
Description

Description:

👉 Download the dataset here

The VSAI (Vehicle Surveillance via Aerial Imagery) Dataset is a highly versatile and expansive collection of high-resolution aerial images gathered from multiple drone platforms. Covering a diverse geographical expanse, this dataset is specifically curated to support vehicle detection tasks in various complex real-world environments. It offers a multi-view perspective of different urban and rural areas, captured under a wide range of conditions.

This unique dataset is designed for advancing object detection in aerial imagery by addressing numerous real-world challenges, such as varying camera angles, diverse flight altitudes, changing weather conditions, and fluctuating light intensities. VSAI captures imagery from different times of the day and seasons, making it an essential resource for building more robust vehicle detection models.

Download Dataset

Dataset Composition

The VSAI dataset contains an impressive 49,712 vehicle instances meticulously annotated using oriented bounding boxes and arbitrary quadrilateral bounding boxes. This level of precision in annotation accommodates varying object shapes and positions in aerial views, enhancing the dataset's utility for training advanced object detection algorithms. It includes annotations for:

Small Vehicles: 47,519 instances

Large Vehicles: 2,193 instances

To enhance model robustness, the dataset also includes detailed annotations of occlusion rates, helping algorithms generalize better under challenging scenarios like partial visibility caused by environmental factors or other objects.

Key Features

Diverse Capture Conditions: The images in VSAI are captured across multiple drone platforms, which vary in altitude, camera angles, and flight paths.

Complex Scenarios: The dataset spans a wide range of environments, including urban centers, rural landscapes, industrial areas, and highways, representing real-world complexities.

Varied Temporal and Weather Conditions: Images have been captured during different times of the day and under diverse weather conditions, including clear skies, overcast, rainy, and foggy environments.

High Annotation Accuracy: Vehicle instances are annotated with highly precise bounding boxes, including both oriented and arbitrary quadrilateral shapes, to reflect the true contours of vehicles as seen from an aerial perspective.

Occlusion Annotation: Objects in the dataset are also labeled with their occlusion levels, providing additional challenges for model training and improving detection performance in scenarios with partially visible vehicles.

This dataset is sourced from Kaggle.

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