Loading...
Loading...
Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
16,270 datasets
lfstat is a software package for calculating low-flow statistics from daily stream flow data. It implements methods described in the World Meteorological Organisation's manual authored by Gustard & Demuth (2009). The package was created by Gregor Laaha.
An R package for analyzing and visualizing directed acyclic graphs (DAGs), built on the 'dagitty' package and the DAGitty web tool. It provides functions to tidy, plot, and analyze DAGs using the 'ggplot2' and 'ggraph' ecosystems. The package was created by author Malcolm Barrett.
Pakistani politicians are the subject of this face recognition dataset. It likely contains images of political figures intended for computer vision tasks. The dataset is published on Kaggle, but specific details about its size, creation date, and author are unknown.
United States national and state-level data on alcohol-attributable deaths and years of potential life lost (YPLL). The dataset is produced by the Centers for Disease Control and Prevention (CDC) and includes estimates by gender, specific medical conditions, and condition type (chronic or acute). ARDI began in 2001, with the most recent data noted as being from 2005.
NOAA Ocean Acidification Program data includes dissolved inorganic carbon, total alkalinity, pH, and nutrients from profile and discrete measurements. Measurements were collected using CTD and Niskin bottle instruments during NOAA Ship Gordon Gunter cruises. The dataset supports coastal monitoring and research on ocean acidification effects in the Northeast US coast.
CycleGan_Head is a dataset hosted on Kaggle, likely containing image data for training or evaluating CycleGAN models. The dataset's specific content, such as the number of images or source domains, is not detailed in the available metadata. Users must download the dataset to verify its exact composition and suitability for their projects.
A curated multi-class waste dataset intended for real-world machine learning training use cases. The dataset likely contains images of different waste categories for classification tasks. Its specific size, source, and creation date are unknown.
A report on violence against children, likely sourced from paperswithcode. The description indicates it aims to inform about the extent of this societal problem and discusses solutions, causes, and recommendations. The author, organization, and specific publication date are unknown.
AdaptiveFlow Ligand Libraries are collections of molecular structures prepared for computational docking simulations. The data is hosted on AWS Open Data and originates from the AdaptiveFlow Project. The last update date and dataset scale are unknown.
World Development Indicators data provides net carbon dioxide fluxes from organic soils. The dataset quantifies emissions and removals from land use, land-use change, and forestry activities. It is compiled by the World Bank.
Five normalized network traffic datasets prepared for quantum machine learning baseline experiments. The datasets are hosted on Kaggle, but specific details about their origin, size, and creation date are not provided in the available metadata.
Rice Leaf Disease Detection Dataset is a hierarchical collection of 7,563 labeled images of rice leaves. The dataset contains 6 classes of diseases and was collected in both laboratory and field settings. The dataset is hosted on Kaggle, but the author, organization, and specific collection dates are unknown.
A dataset of ECG (electrocardiogram) signals, likely processed with Generative Adversarial Networks (GANs). The title suggests the data may involve noisy segment regularization and adversarial training techniques. It is hosted on Kaggle, but the original author and collection details are unspecified.
ECGID_NO_PGD_GAN_PER_NOISY_SEGMENT_REG_v2 is a dataset published on Kaggle. The title suggests it contains electrocardiogram (ECG) signal data, likely processed or augmented using Generative Adversarial Networks (GANs). No further details on size, source, or specific contents are available from the provided metadata.
VinBigData is a dataset of medical images formatted for YOLO object detection training. It is hosted on Kaggle, but the specific number of images, rows, and creation details are not provided in the available metadata. The dataset's content and scale require verification after download.
A video sequence from the MOT17 benchmark, likely used for evaluating multi-object tracking algorithms. The dataset is published on Kaggle, though its specific creation date and author are unknown. It appears to be part of a standard computer vision benchmark for tracking pedestrians or vehicles.
Kaggle hosts a dataset titled 'imagenet_weights'. The dataset likely contains pre-trained model weights derived from the ImageNet dataset, a large-scale image database used for visual object recognition research. The author, organization, and specific details about the weights' format and version are unknown.
YOLO Phase 3 is a dataset hosted on Kaggle, likely containing images annotated for object detection tasks. The dataset's specific contents, scale, and origin are not detailed in the available metadata. Users must download the dataset to verify the number of images, annotation format, and licensing information.
A dataset published on Kaggle, likely containing images for training or evaluating YOLO (You Only Look Once) object detection models. The author, organization, and specific details such as size and license are unknown. The last update date is also unknown.
Olmocr Bench English is a document text extraction benchmark containing 6,483 English-only test cases across seven specialized categories including mathematical notation and complex layouts. Created by sarvamai as a filtered version of the allenai/olmOCR-bench dataset, it provides a targeted evaluation set for OCR models updated as of February 2026. The collection focuses on challenging document elements such as multi-column text, tables, and historical scans.