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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
16,095 datasets
VSL400 keypoint test batch 2 is a dataset published on Kaggle. Its title suggests it contains images annotated with keypoints, likely for testing computer vision models. The dataset's specific content, size, and origin are not detailed in the available metadata.
A dataset likely containing medical images for training convolutional neural network models to diagnose pneumonia. It was published on Kaggle, but its specific source, size, and creation date are unknown. The exact number of images and their provenance require verification after download.
OCR Checkpoint is a dataset published on Kaggle. Its title suggests it contains model weights or training checkpoints for an Optical Character Recognition system. The dataset's specific content, scale, and origin are not detailed in the available metadata.
5 million records describe missions and activities from 10 elite global intelligence organizations. The dataset, sourced from Kaggle, appears to cover covert operations and spy agency work. Details on the data's origin, collection method, and time period are not provided in the available description.
YOLO10s is a dataset likely intended for training and evaluating object detection models. It is published on Kaggle, but its specific contents, size, and creation details are not documented. The dataset's last update date, author, and license are unknown.
A subset of the Intel Image Classification dataset containing 10,000 images. The data is organized into four scene classes from natural environments. The dataset is hosted on Kaggle, but its original author, organization, and collection date are unknown.
The dataset titled 'mss-gan-code' is hosted on Kaggle. Its specific contents are not detailed, but the name suggests a connection to Generative Adversarial Networks, a class of machine learning models. The author, organization, and temporal coverage are unknown.
A sample of Arabic dialect text likely collected from organic, real-world sources. The dataset is hosted on Kaggle, but its author, size, and specific collection date are unknown. Columns and detailed content require verification after download.
Lührmann et al. (2018) provide a classification of political regimes based on expert estimates from the Varieties of Democracy (V-Dem) project. The dataset likely contains categorical labels distinguishing democracies and autocracies. The classification methodology relies on expert assessments rather than simple binary indicators.
2013 monthly samples from eight Welsh upland rivers with contrasting moorland and conifer land-use, examining benthic organic matter stocks. The experiment manipulated riparian deciduous leaf addition across control and treatment reaches. Data collection was organized by Dr Isabelle Durance under the NERC-funded DURESS project.
Eight Welsh upland river reaches were sampled to examine macroinvertebrate composition and abundance in response to deciduous leaf addition. The survey, conducted in January and March 2013, compared moorland and conifer forested sites at Llyn Brianne and Plynlimon. Dr Isabelle Durance organized the work under the NERC-funded DURESS project.
A collection of medical images related to Pap smear tests, likely for cytology analysis. The dataset was published by MarrLab on the Hugging Face platform and was last updated on 2026-04-14. The specific content, scale, and format require verification after download.
Model checkpoints for the BirdCLEF 2026 competition. The checkpoints likely represent trained models for bird species identification from audio recordings. They were published on Kaggle.
A dataset for applying graphical Innovative Trend Analysis and statistical methods like the Sequential Mann-Kendall test to identify trends and change points in time series data. The dataset is associated with research by Sandeep Kumar Patakamuri and references foundational works in hydrology and climatology. It is hosted on the paperswithcode platform.
Encompassing approximately 17,000 video clips organized into 9 chunks of roughly 2,000 clips each. It includes processed outputs such as cropped faces, restored faces, and final results from experiments, intended for computer vision research.
A dataset likely containing annotated images for computer vision tasks. It is published on Kaggle, but the author, organization, and last update date are unknown. The dataset's name suggests it is related to the YOLOv11 model and the COCO (Common Objects in Context) benchmark, potentially for segmentation tasks.
A dataset titled 'hagrid-yolo-det2of3' published on Kaggle. The title suggests a focus on object detection, likely using the YOLO framework. No further metadata is available to confirm its specific contents, size, or origin.
Cleaned VisDrone YOLO Dataset is a computer vision dataset published on Kaggle. The dataset title suggests it contains drone-captured imagery formatted for YOLO object detection models. Specific details on size, columns, and origin are not provided in the available metadata.
A dataset titled 'ckp_GuwenBert_nomnaocr_repair_stage1_aug_e1_30_v11' is hosted on Kaggle. The title suggests it contains Chinese text data, likely related to a BERT model checkpoint or training corpus. Metadata is minimal; the specific content, size, and origin require verification after download.
Kaggle hosts a dataset titled DogandCat. Its content likely pertains to images of dogs and cats, which suggests it is a resource for computer vision tasks. The dataset's author, organization, and specific details are unknown.