Loading...
Loading...
Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
16,346 datasets
Yolo26n_Unetpp appears to be a dataset for training or benchmarking computer vision models, specifically those combining YOLO object detection and UNet++ segmentation architectures. It was published on Kaggle, but the author, organization, and specific data characteristics are not provided. The title suggests the data may be related to a model trained for 25 epochs.
Preprocessed 256x256 PNG images and masks for medical image segmentation tasks. The dataset appears to be derived from the LiTS (Liver Tumor Segmentation) benchmark. The original source, author, and specific size are unknown.
Featuring research data from a study on middle managers in strategic processes and practices within the Brazilian manufacturing industry. The data was used for a paper published in Revista Brasileira de Gestão de Negócios in 2026. The author is Regina Célia Zimmermann da Fonseca.
YOLO is a dataset for object detection tasks, published on Kaggle. The dataset's specific content, size, and features are not detailed in the available metadata. Further verification after download is required to confirm its exact composition and suitability for specific projects.
Electronics YOLO Dataset is a computer vision collection published on Kaggle. The dataset's title suggests it contains images of electronic items annotated for object detection tasks using the YOLO framework. Its specific content, scale, and creation details require verification after download due to minimal provided metadata.
A dataset related to the ArcFace method for face recognition, published on Kaggle. The specific content, scale, and authorship are not detailed in the provided metadata. Its intended use is likely for training or benchmarking face recognition models.
Atmospheric volatile organic compounds (VOCs) measured in Shenyang, China. The dataset's size, collection period, and author are not specified in the provided metadata. It was sourced from the Kaggle platform.
331 SEM images of microbial-induced corrosion (MIC) collected by Robert McLean from the NASA SpaceX-21 mission. The dataset includes both flight and ground control conditions with corresponding segmentation annotations for corrosion detection. It was last updated in February 2026 to support maintenance planning and corrosion mitigation research.
10,000 images of faces labeled as real or fake, intended for training AI classifiers. The fake images are generated using NVIDIA's StyleGAN3 model. The dataset's provenance, size, and license details are unknown.
An OCR project dataset published on Kaggle. The dataset likely contains images of documents and corresponding text for optical character recognition tasks. Specific details on size, source, and creation date are not provided in the available metadata.
A dataset bundle likely intended for training object detection models, specifically using the YOLO (You Only Look Once) framework. It is hosted on Kaggle, but its specific contents, size, and origin are not detailed in the available metadata. The 'stage1' label suggests it may be part of a multi-phase training or competition pipeline.
A dataset titled 'model_VGG2D.py' is hosted on Kaggle. The dataset's content likely relates to a VGG-style 2D convolutional neural network architecture, as suggested by the filename. No further metadata on size, columns, or origin is available.
A dataset from Kaggle containing outputs from training computer vision models. The title suggests it includes results from a YOLO26n object detection model and a SegFormer semantic segmentation model, each trained for 25 epochs. The specific data content, such as model weights, logs, or evaluation metrics, requires verification after download.
model_VGG2D is a dataset published on Kaggle, a popular platform for data science competitions. The title suggests a connection to the VGG convolutional neural network architecture, commonly used for image recognition tasks. No further metadata on size, source, or content is available.
A demonstration dataset titled 'IPPOCRATE_Demo_Dataset' published on Kaggle. The dataset's specific content, size, and origin are not detailed in the available metadata. Its title suggests a medical or healthcare theme, likely intended for demonstration purposes.
Kaggle hosts a set of YOLOv8 model weights for object detection. The dataset likely contains the trained parameters for detecting Crown-of-Thorns Starfish (COTS) in underwater imagery. Specific details on the training data, performance, and author are not provided in the available metadata.
Armin Schäfer published this social science replication dataset in 2026 via Harvard Dataverse to support the study 'Losers' Dissent: How Election Results Shape Populists’ Satisfaction with Democracy.' The data enables the reproduction of statistical findings regarding the relationship between electoral outcomes and democratic satisfaction among populist voters.
A paper providing an overview of research into the complexity and diversity of youth gangs. It discusses distinctions between youth groups and gangs, categorizes gang behaviors, and examines factors in gang formation and disintegration. The paper originates from the paperswithcode platform.
Areas degraded by mining, cultivation, and livestock in Colombia's Chocó Department are documented with coordinates and hectares. The dataset is provided by the environmental authority of Chocó via the Colombian open data portal. It was last updated in December 2025.
5,082 email threads extracted from documents released by the U.S. House Oversight Committee. The dataset has been processed with large language models to structure information including senders, recipients, timestamps, subjects, and message bodies.