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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
16,345 datasets
Survey data from the Global Financial Inclusion and Consumer Protection Survey, published on the World Bank platform. The dataset likely contains information on whether authorization is required for new or modified financial products offered by microcredit institutions. Columns may suggest regulatory compliance statuses and institutional characteristics.
The Global Financial Inclusion and Consumer Protection Survey dataset titled '210_For microcredit institutions (MCIs), is authorization of new or modified financial products never explicitly required?' originates from the World Bank. It likely contains survey responses from microcredit institutions regarding regulatory requirements for financial product authorization. The specific number of rows, columns, and temporal coverage is unknown from the provided metadata.
208_For microcredit institutions (MCIs), is authorization of new or modified financial products always explicitly required? is a dataset from the World Bank's Global Financial Inclusion and Consumer Protection Survey. The dataset likely contains survey responses or regulatory information concerning authorization requirements for financial products offered by microcredit institutions. Its specific scale, time range, and detailed content are not provided in the available metadata.
Global Financial Inclusion and Consumer Protection Survey data examines the existence of regulatory frameworks for microcredit institutions. The dataset likely contains survey responses from multiple countries, focusing on the supervisory environment for MCIs. Its specific scale, row count, and temporal coverage are not detailed in the available metadata.
World Bank survey data investigating regulatory requirements for product information disclosure by microcredit institutions. The dataset originates from the Global Financial Inclusion and Consumer Protection Survey. Its specific temporal and geographic coverage is not detailed in the available metadata.
Images of food items categorized as healthy or unhealthy. The dataset is hosted on Kaggle, but its size, creation date, and author are unknown. Columns and specific contents require verification after download.
FinMTM is a multi-turn multimodal benchmark for financial reasoning and agent evaluation. It contains image and text data, with over 10,000 instances indicated by its 'Size Categories1 Kn10 K' tag. The dataset was created by researchers from HiThink Research, Wuhan University, Zhejiang University, Nanyang Technological University, and Shanghai Institute of Technology.
A set of pre-trained weights for the YOLOv5m model architecture. The dataset is hosted on Kaggle, but its specific source, creation date, and the exact training data used are not provided. The content likely contains the learned parameters for detecting objects in images.
Industrial Rooms (LR) is a dataset of synthetic images designed for 2D object detection tasks. The dataset likely contains computer-generated scenes depicting industrial environments. Its author, organization, and specific size are unknown.
Regensburg LR is a synthetic image dataset for 2D object detection tasks. The dataset likely contains computer-generated images simulating objects within an automotive factory logistics environment. Its author, organization, and specific scale are unknown.
An OCR-ready, filtered version of the RUKOPYS dataset. The dataset is hosted on Kaggle, but the author, organization, and specific collection details are unknown. The original RUKOPYS dataset likely contains Ukrainian text documents prepared for optical character recognition tasks.
YOLOv8m is a dataset published on Kaggle. The title suggests it is related to the YOLOv8m computer vision model, which is typically used for object detection tasks. The dataset likely contains images and annotations for training or evaluating such a model.
YOLOv8 is a dataset related to the YOLO (You Only Look Once) family of object detection models. It was published on Kaggle, but the specific contents, size, and creation details are not provided in the available metadata. The actual data composition, including the number of images and annotations, requires verification after download.
A dataset titled 'detecttomato.v2i.yolo26(sai_gon)' suggests a collection of images for detecting tomatoes. It is hosted on Kaggle, a platform for data science and machine learning projects. The dataset's format and annotation style are likely tailored for training YOLO-based object detection models.
OCR_OpenViVQA is a dataset hosted on Kaggle. The dataset's title suggests it combines optical character recognition (OCR) with visual question answering (VQA) tasks. Metadata regarding its size, structure, and origin is currently unavailable.
A fork of a CycleGAN implementation with a tunable U-Net architecture, published on Kaggle. The dataset likely contains code and model configurations for image-to-image translation tasks. Specific details about the data volume, author, and last update are not provided in the available metadata.
ImageNet_classes is a dataset listing the 1000 object categories used in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC). It is published on the Kaggle platform. The specific source, author, and update history for this particular listing are unknown.
Kaggle hosts this dataset titled 'yolo_lang_dataset_2'. The title suggests it likely contains images for training or evaluating YOLO (You Only Look Once) object detection models, potentially combined with language-related annotations. The dataset's author, organization, size, and specific content are unknown.
Full Code Using Mask RCNN is a dataset published on Kaggle. The title suggests it relates to the Mask R-CNN architecture for object detection and instance segmentation. The dataset's specific content, size, and origin are not detailed in the provided metadata.
512_yolov12n_weights is a dataset of pre-trained model weights for a YOLO (You Only Look Once) object detection architecture. The dataset is hosted on the Kaggle platform. The specific architecture version, training data, and performance metrics are not detailed in the available metadata.