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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
17,713 datasets
Over 360,000 document images from the PubMed Central Open Access Subset with layout annotations. It provides both bounding boxes and polygonal segmentations for document elements, generated by programmatically matching PDF visual layouts with XML structural data.
Housing five standard datasets for few-shot classification, including miniImageNet and tieredImageNet. The miniImageNet dataset has 100 classes with 600 images each, partitioned into 64, 16, and 20 classes for meta-training, validation, and testing. The tieredImageNet dataset includes 608 classes grouped into 34 super-classes, with splits of 20, 6, and 8 classes for the respective meta-learning phases.
An index from the NIST Physical Measurement Laboratory provides access to online scientific data organized by chemical element. It simplifies retrieval from databases covering atomic spectroscopy, atomic data, x-ray absorption, and nuclear data. The data is maintained by the National Institute of Standards and Technology and was last updated in July 2022.
SRD 69 from the National Institute of Standards and Technology provides thermochemical, thermophysical, and spectral data for chemical species. The database includes properties like enthalpy, boiling point, ionization potential, and mass spectra. It was last updated in July 2022.
CLIP-Kinetics700 is a compressed version of the Kinetics700 dataset, using OpenAI's CLIP model to encode video frames. The original ~700 GB dataset was reduced to ~8 GB by downsampling videos to 1 frame per second. It was created by iejMac and last updated in July 2022.
Created by jayleicn and last updated in August 2022, this repository provides a PyTorch implementation of Generative Adversarial Networks (GANs) for anime face drawing. It includes the framework and image data necessary to train models on stylized character illustrations.
Encompassing images of Egyptian hieroglyphs extracted from 10 specific pictures in the 1955 book 'The Pyramid of Unas' by Alexandre Piankoff. It was created by HamdiJr and includes an associated language model. The specific page images used are numbered 3, 5, 7, 9, 20, 21, 22, 23, 39, and 41 from the source book.
12,000+ labeled images across 15 distinct human activity classes. The dataset includes training and validation subsets where each image is assigned a single activity label based on its directory location.
Model predictions for a summarization task on the Dutch version of the CNN/DailyMail dataset. The predictions were generated by the AutoTrain Evaluator using the yhavinga/mt5-base-mixednews-nl model on the test split. The evaluation job was contributed by @yhavinga and last updated on August 2, 2022.
AutoTrain Evaluator contains model predictions for a summarization task on the Dutch version of the CNN/DailyMail dataset. The predictions were generated by the yhavinga/mt5-base-cnn-nl model on the test split. This evaluation snapshot was created by autoevaluate and uploaded on August 2, 2022.
health.data.ny.gov provides two datasets with 99 state-level health tracking indicators for the Prevention Agenda 2019-2024. The data includes metrics for chronic disease, mental health, communicable diseases, and health disparities, organized by Priority and Focus Areas. Each indicator includes a 2024 objective, confidence intervals, and historical trend data where available.
Urban drone imagery and semantic constraints facilitate large-scale Structure from Motion (SfM) research. The data provides specific semantic labels to improve 3D reconstruction accuracy as presented in PRCV2018.
Comprising model predictions for a summarization task on the Dutch version of the CNN/DailyMail dataset. The predictions were generated by the model 'yhavinga/t5-v1.1-base-dutch-cnn-test' on the test split. The specific number of rows, columns, and data size are unknown.
A collection of model predictions for a summarization task on the CNN DailyMail dataset. The predictions were generated by the pszemraj/long-t5-tglobal-base-16384-booksum-V11-big_patent-V2 model on the test split. The number of rows, columns, and specific data fields are unknown.
Containing 10,200 images of aircraft, with 100 images for each of 102 different aircraft model variants. Each image includes a tight bounding box annotation and a hierarchical label spanning model, variant, family, and manufacturer levels. The data is pre-split into equally-sized training, validation, and test subsets.
Encompassing approximately 1000 images of pizza and 1000 images of non-pizza dishes, totaling around 2000 images for a binary classification task. All images are rescaled to a maximum side length of 512 pixels. It is a curated subset of the Food-101 dataset, created by nateraw.
Aggregating model predictions for a summarization task on the CNN DailyMail dataset, generated by the nbroad/longt5-base-global-mediasum model. The data is from the test split using dataset config 3.0.0. The number of rows, columns, and specific data fields are unknown.
Model predictions generated by AutoTrain for a summarization task on the CNN/DailyMail dataset. The predictions were produced by the sshleifer/distilbart-cnn-6-6 model on the test split of the dataset version 3.0.0. The specific row count, column structure, and sample data are unknown.
A collection of model predictions generated by AutoTrain for a summarization task on the CNN DailyMail dataset. The predictions are from the model 'philschmid/distilbart-cnn-12-6-samsum' evaluated on the test split of the dataset. The number of rows, columns, and specific data fields are unknown.
Encompassing model predictions generated by AutoTrain for a summarization task on the CNN/DailyMail dataset. The predictions were produced by the sshleifer/distilbart-cnn-12-6 model on the test split of the dataset. The specific number of rows, columns, and data size are unknown.