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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
16,020 datasets
A Kaggle dataset titled 'my-yolo-lite-project-2' suggests a collection of images for object detection tasks. The project's name indicates it is likely intended for training or benchmarking lightweight YOLO (You Only Look Once) models. No information is available on its size, creator, or creation date.
Kaggle hosts a dataset titled 'CNN for malware'. The dataset likely contains image-based representations of malware for use with Convolutional Neural Networks. Its specific size, origin, and creation date are unknown from the provided metadata.
A dataset for self-supervised learning in computer vision, likely containing images of plants. The dataset is hosted on Kaggle and appears to be designed for training models like ResNet10t. Its specific source, collection method, and scale are not detailed in the provided metadata.
Discrete profile measurements for the ChΓ‘ BΔ mooring time-series validation were collected on cruise TN264 aboard the R/V Thomas G. Thompson on 2011-05-22. The dataset includes dissolved inorganic carbon, total alkalinity, temperature, salinity, oxygen, and nutrient data from Niskin bottle samples and CTD sensors. This effort was conducted by NOAA's Ocean Acidification Program in support of coastal monitoring and conforms to Global Ocean Acidification Observing Network guidelines.
Page images from historical Japanese documents (Kotenseki) are provided with character-level bounding box annotations for Kuzushiji (cursive Japanese) recognition. The dataset was uploaded by Kotomiya07 and was last updated on March 10, 2026.
2,548 human motion capture animations in FBX format are available, derived from the CMU Graphics Lab Motion Capture Database. The library is organized by subject and motion number. It was uploaded by author 'gbionics' and last updated on March 5, 2026.
Syringe collection records from New York City parks, detailing collection methods and dates. Data is collected by NYC Parks staff and partner organizations like the Washington Heights Corner Project and New York Harm Reduction Educators. The dataset is part of the NYC Parks Syringe Litter Data Collection initiative.
Synthetic maze and real-world image maps for robot path planning. The dataset is hosted on Kaggle, but details on its creator, size, and specific creation date are unknown. It likely contains image-based maps designed for training and evaluating path-finding algorithms.
Fugro collected a post-storm LiDAR survey commissioned in March 2022 for soft sedimentary areas on the north coast of Northern Ireland. The data includes a Digital Terrain Model for Curran Strand, Portrush East Strand, Portstewart Strand, and Downhill Beach to Magilligan. It was provided in the same format as a 2021 baseline survey to ascertain coastal changes following Storm Dudley, Eunice, and Franklin.
A March 2022 LiDAR and natural color orthophotography survey of soft sedimentary coastlines in Northern Ireland, commissioned by Fugro following Storm Dudley, Eunice, and Franklin. The data covers Curran Strand, Portrush East Strand, Portstewart Strand, and Downhill Beach to Magilligan. It was collected to assess coastal change against a 2021 baseline survey and is provided by OpenDataNI under the OGL-UK-3.0 license.
Fugro conducted a post-storm LiDAR survey in March 2022 commissioned to assess coastal damage along the north coast of Northern Ireland. The data covers soft sedimentary areas including Curran Strand, Portrush East Strand, Portstewart Strand, and Downhill Beach to Magilligan. This Digital Terrain Model is provided by OpenDataNI to allow comparison with a baseline survey from 2021.
A Digital Terrain Model (DTM) created from a LiDAR survey commissioned by Fugro in March 2022. The survey covers soft sedimentary areas along the north coast of Northern Ireland, including Curran Strand and Portstewart Strand, to assess coastal change following storms Dudley, Eunice, and Franklin. Data is provided in a format consistent with a 2021 baseline survey to enable change detection.
A March 2022 natural colour orthophotography dataset captured by Fugro following storm events Dudley, Eunice, and Franklin. The survey covers soft sedimentary areas along the north coast of Northern Ireland, including Curran Strand, Portrush East Strand, Portstewart Strand, and Downhill Beach to Magilligan. It was commissioned to ascertain coastal change since a 2021 baseline survey and provided in a format consistent with a 3-Dimensional Coastal Survey for comparison.
A LiDAR survey commissioned by Fugro in March 2022 captured the soft sedimentary coastlines of Northern Ireland's north coast after successive storms. The data, provided in the same format as a 2021 baseline survey, allows for change detection. This dataset is the Digital Surface Model created from that post-storm LiDAR data.
A post-storm LiDAR survey commissioned by Fugro in March 2022 covered four soft sedimentary areas along the north coast of Northern Ireland: Curran Strand, Portrush East Strand, Portstewart Strand, and Downhill Beach to Magilligan. The survey aimed to ascertain coastal change following Storm Dudley, Storm Eunice, and Storm Franklin, with data provided in the same format as a 2021 baseline survey. This specific dataset is the Natural Colour Orthophotography captured as part of that survey.
Natural Colour Orthophotography captured via a LiDAR survey commissioned by Fugro in March 2022. The survey covers soft sedimentary coastlines at Curran Strand, Portrush East Strand, Portstewart Strand, and Downhill Beach to Magilligan. Data was collected to assess changes caused by Storm Dudley, Storm Eunice, and Storm Franklin relative to a 2021 baseline survey.
Fugro conducted a post-storm LiDAR survey in March 2022 of soft sedimentary coastlines along the north coast of Northern Ireland. The survey covers Curran Strand, Portrush East Strand, Portstewart Strand, and Downhill Beach to Magilligan to assess changes from a 2021 baseline following Storm Dudley, Eunice, and Franklin. This dataset is the Digital Surface Model created from that post-storm LiDAR data, provided by OpenDataNI.
Monthly counts of inquiries made to the Seattle Office for Civil Rights (SOCR) regarding potential civil rights law violations. The dataset is published by the City of Seattle on the Data.gov platform and was last updated on March 15, 2026. The data likely contains a time series of inquiry volumes.
A dataset hosted on Kaggle, likely intended for training object detection models. The title suggests it may be designed for use with Faster R-CNN (FRCNN) architectures, potentially for few-shot learning (FS). The dataset's specific contents, size, and origin are not detailed in the provided metadata.
A base model derived from the ImageNet dataset, published on Kaggle. The dataset likely contains image data and associated labels for classification tasks. Specific details on size, format, and version are not provided in the available metadata.