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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
16,302 datasets
PL_Shrimp_Datomate_YOLO is a computer vision dataset likely containing images of shrimp for object detection tasks. The dataset is hosted on Kaggle, but its specific contents, size, and creation details are not documented. The title suggests it is formatted for use with the YOLO (You Only Look Once) object detection framework.
A dataset likely containing images for object detection tasks related to welding. It is published on Kaggle, but the specific number of images, creation date, and author are unknown. The title suggests the data is balanced for training YOLO models.
High-resolution electron microscopy images of subcellular structures, published on the AWS Open Data registry. The dataset is provided by the Janelia Research Campus and is licensed under CC-BY-4.0.
YOLOv8 is a dataset published on Kaggle. The dataset likely contains images and annotations for training and evaluating object detection models. Its specific content, size, and creation details are not provided in the available metadata.
ResNet is a dataset hosted on Kaggle. Its title suggests it is related to the ResNet (Residual Network) architecture, a foundational model in computer vision. The dataset likely contains images intended for classification tasks, but its specific content, size, and origin are not detailed in the provided metadata.
Kaggle hosts this dataset titled 'resnett'. The dataset's name suggests a connection to ResNet architectures, which are commonly used for image recognition tasks. Its content and scale are not described in the provided metadata.
YOLO_5 is a dataset hosted on Kaggle. Its title suggests it is likely related to the YOLO (You Only Look Once) family of object detection models. The dataset's specific content, scale, and origin are not detailed in the provided metadata.
Numerical data and gnuplot scripts representing complex dispersion lines in gapped bilayer graphene, authored by Ryo Tamura in 2026. It contains the underlying values for Figures 3 through 10 of the manuscript arXiv:2602.20589, stored in plain text format for scientific reproduction.
Poland's Borzęcin gas reservoir, operational since the 1970s, was sampled in May 2019 from two wells. The dataset contains analyses of gas composition and stable isotopes, created within the EU-funded SECURe project. The British Geological Survey is the organizing body.
Bucaramanga's public health enterprise (ESE) organized approximately 143,000 subsidized-regime users across 22 health centers based on their residential location. The dataset allows identification of the assigned population per health center by age, gender, life cycle, and health insurer (EPS). The data was published by datos.gov.co and was last updated in December 2025.
Kaggle hosts a dataset associated with the VGG16 convolutional neural network architecture. The dataset likely contains image data or model weights used for training or benchmarking. Metadata is minimal; the exact content, size, and provenance require verification after download.
Kaggle dataset titled LO_LightGBM_Smote_Gan_Results. The title suggests it contains results from a LightGBM model trained using SMOTE and GAN techniques. The dataset's author, organization, and specific content are unknown.
997 annotated images for multi-class vehicle detection in traffic scenes. The dataset is formatted for training YOLOv8 object detection models. It was sourced from Kaggle, but the author, license, and collection details are unknown.
A collection of 997 annotated images for multi-class vehicle detection in traffic scenes. The dataset is formatted for training YOLOv8 object detection models. The author, organization, and specific collection details are not provided.
Kaggle hosts a dataset titled 'efficientnetv2'. The dataset likely contains the pre-trained weights or configuration for the EfficientNetV2 convolutional neural network architecture. The author, organization, and last update date are unknown.
Replication Data for a study by Roderik Rekker of the University of Amsterdam investigates the effect of prosecuting politicians for hate speech on public support for the legal system and democracy. The study combines three research designs—an experiment, a quasi-experiment, and a nine-year panel study—focused on the 2016 conviction of Dutch politician Geert Wilders. The data likely contains survey and panel responses measuring support levels among different voter groups before and after the verdict.
The CIRI Human Rights Dataset provides standards-based quantitative information on government respect for 15 internationally recognized human rights. It covers 202 countries annually from 1981 to 2011. David Cingranelli of Binghamton University created the dataset with support from the National Science Foundation.
This dataset, published on Kaggle, likely contains pre-trained model weights for the ECA-NFNet-L0 and EfficientNet architectures from the Timm (PyTorch Image Models) library. The specific contents, such as the number of model files or their training details, are not described in the available metadata. The dataset's author, organization, and last update date are unknown.
BiLSTM(Dask)_Smote_Gan_Result is a dataset published on Kaggle. The title suggests it contains results from a machine learning experiment involving a Bidirectional LSTM (BiLSTM) model, Dask for distributed computing, SMOTE for data balancing, and a Generative Adversarial Network (GAN). The dataset's content, scale, and authorship are unknown.
Kaggle hosts a dataset likely containing images for training or evaluating the YOLOv3 object detection model. The dataset's specific contents, size, and origin are not detailed in the provided metadata. Further details such as the number of images, annotation types, and creation date are unknown.