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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
15,947 datasets
St Clair and Marine City, Michigan, are covered by ortho-rectified mosaic tiles produced by the NOAA National Geodetic Survey. The source imagery was captured on July 23, 2019, using an Applanix Digital Sensor System (DSS) as part of the Integrated Ocean and Coastal Mapping initiative. The original high-resolution aerial photographs were processed to create the final corrected mosaic.
NOAA's National Geodetic Survey produced this ortho-rectified mosaic from aerial imagery acquired between September 12 and 15, 2016. The data is a product of the Integrated Ocean and Coastal Mapping initiative, using an Applanix Digital Sensor System. The source images were acquired at a higher resolution to support the final mosaic product.
An ortho-rectified color mosaic of Marine City, Marysville, and Port Huron, Michigan, created by the National Oceanic and Atmospheric Administration (NOAA). The source imagery was acquired on September 12, 2016, using an Applanix Digital Sensor System (DSS) as part of the Integrated Ocean and Coastal Mapping initiative. The data is provided as ortho-rectified mosaic tiles.
A 2018 ortho-rectified color mosaic of St. Joseph, Michigan, created by the NOAA Integrated Ocean and Coastal Mapping initiative. The source imagery was acquired on May 16, 2018, using a Trimble Digital Sensor System from an airplane. The final product is a georeferenced image mosaic intended for coastal mapping and analysis.
NOAA's National Geodetic Survey produced an ortho-rectified color mosaic of Manistee, Michigan. The source imagery was acquired from September 12 to 15, 2016, using an Applanix Digital Sensor System (DSS) as part of the Integrated Ocean and Coastal Mapping initiative. The final mosaic is composed of higher-resolution original images.
A 4-band ortho-rectified mosaic of Waukegan, Illinois, created by the NOAA National Geodetic Survey. The source imagery was captured on October 3, 2022, using a Digital Sensor System (DSS) Version 6 as part of the Integrated Ocean and Coastal Mapping initiative. The data is provided as tiles, with the original images acquired at a higher resolution to support the final mosaic product.
NOAA's National Geodetic Survey produced an ortho-rectified mosaic from aerial imagery captured on November 13, 2016. The data covers the coastal areas of Muskegon, Grand Haven, and Holland in Michigan. It was created under the Integrated Ocean and Coastal Mapping initiative using an Applanix Digital Sensor System.
Ortho-rectified mosaic tiles were created from aerial imagery acquired between September 2010 and September 2011. The National Oceanic and Atmospheric Administration produced this data through its Integrated Ocean and Coastal Mapping initiative. Original images were captured with an Applanix Digital Sensor System at a higher resolution than the final mosaic.
A 4-band ortho-rectified mosaic of coastal Michigan, created by the NOAA National Geodetic Survey. The source imagery was acquired from August 3 to August 14, 2024, using an Applanix Digital Sensor System (DSS) mounted on an airplane. This dataset is a product of the NOAA Integrated Ocean and Coastal Mapping (IOCM) initiative.
NOAA's 2016 ortho-rectified color mosaic provides geospatially accurate aerial imagery of Monroe, Michigan. The imagery was captured on November 12, 2016, using an Applanix Digital Sensor System (DSS) as part of the Integrated Ocean and Coastal Mapping initiative. This dataset is produced by the National Oceanic and Atmospheric Administration's National Geodetic Survey.
NOAA NGS ortho-rectified color mosaic tiles were produced under the Integrated Ocean and Coastal Mapping initiative. The source imagery was acquired on September 20, 2016, using an Applanix Digital Sensor System. The original images were captured at a higher resolution to support the final mosaic product.
An instruction dataset for crop disease diagnosis and organic treatment. The dataset is described as high-quality and is hosted on Kaggle. Its specific size, origin, and update history are not detailed in the available metadata.
Historical-only data on swim advisories issued by the Chicago Park District for Lake Michigan beaches. Advisories are based on predicted E. coli levels exceeding 235 Colony Forming Units per 100 ml of water. The dataset is linked to related data sources for prediction inputs and later measured levels.
New York State Office of Parks, Recreation and Historic Preservation (OPRHP) provides annual attendance figures for its facilities. The data is organized by OPRHP region, county, and specific facility, beginning in 2003. It covers over 250 state parks, historic sites, and recreational facilities visited by an estimated 74 million people annually.
Raw data from Michigan International Speedway covering the 2022 to 2026 period, coinciding with NASCAR's Next Gen car era. The dataset's origin and specific contents are not detailed, but it likely contains race statistics and telemetry. It is hosted on Kaggle, a platform for sharing datasets.
10,000 augmented images likely containing Tifinagh script, published on HuggingFace by Tamazight. The dataset was last updated on 2026-05-14. Columns suggest it contains image data and possibly text annotations for optical character recognition tasks.
alertreck-cnn-checkpoint is a dataset hosted on Kaggle. The title suggests it contains a checkpoint file for a Convolutional Neural Network (CNN) model, likely for computer vision tasks. The dataset's specific contents, such as the model's architecture, training data, or performance, require verification after download.
A dataset named 'metricgan_chebyshev' published on Kaggle. The title suggests a focus on audio signal enhancement, likely using a GAN-based model with a Chebyshev distance metric. The dataset's specific content, size, and origin are not detailed in the provided metadata.
FLUX+LoRA synthetic sonar images for YOLO detection. The dataset appears to be a collection of artificially generated side-scan sonar images. Its author, organization, and size are unknown.
MetricGAN-WavKan is a dataset likely related to speech enhancement using Generative Adversarial Networks. It is hosted on Kaggle, a platform for data science competitions and projects. The specific contents, such as audio samples or training data, require verification after download.