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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
16,270 datasets
Eight lake sediment cores from Greater Glasgow, Scotland, provide measurements of metals and radionuclides dated from the mid-19th century to 2016. The dataset includes a standardized matrix of sediment variables such as mercury, nickel, copper, zinc, and lead concentrations against stratigraphic depth. Radionuclide dating using 210Pb, 137Cs, and 241Am establishes a reliable chronology for environmental change analysis.
Modelled estimates of Biological Monitoring Working Party (BMWP) scores for freshwater streams across Great Britain. Data pools observations from two survey years, 1998 and 2007, to model relationships between stream quality and catchment characteristics using a Boosted Regression Tree approach.
Great Britain's index to external site investigation reports, dating back to the 1950s. The collection, established in 1988 by the British Geological Survey, covers reports containing information on boreholes, trial pits, laboratory tests, and chemical analyses.
A dataset named YOLO26M, published on Kaggle. The title suggests it is a large-scale collection of images for object detection tasks, likely intended for training and evaluating YOLO (You Only Look Once) models. The dataset's specific contents, size, and creation details are not provided in the available metadata.
CelebFace is a dataset for face detection tasks, likely containing images of public figures. It is hosted on the Kaggle platform, but its specific size, creation date, and authorship are unknown. The dataset's content and structure must be verified after download.
A dataset titled 'sealife_yolo' hosted on Kaggle. The dataset likely contains images annotated for object detection using the YOLO (You Only Look Once) framework, focusing on marine life. Its specific contents, scale, and origin are unconfirmed due to minimal provided metadata.
A dataset published on Kaggle, likely containing images for object detection tasks. The dataset's specific content, size, and creation details are not provided in the available metadata. Users must download the dataset to verify its exact composition and suitability for their projects.
YOLO_detector is a dataset hosted on Kaggle. Its content likely pertains to object detection, a core computer vision task. The dataset's specific size, origin, and update history are not provided in the available metadata.
Kaggle hosts this image collection intended for computer vision tasks. The dataset likely contains photographs of six types of seafood for classification model development. Its author, organization, and specific details like size and license are not provided in the metadata.
A dataset published on Kaggle for use with Generative Adversarial Networks (GANs). The dataset's specific content, size, and creation details are not described in the available metadata. Users must download the dataset to verify its actual contents and suitability for their projects.
ECGID_NO_PGD_GAN_PER_NOISY_SEGMENT_REG_V3 is a dataset published on Kaggle. Its title suggests a focus on electrocardiogram (ECG) signals, likely processed or generated using Generative Adversarial Networks (GANs). The dataset's specific content, size, and origin require verification after download due to minimal provided metadata.
Kaggle hosts this dataset titled 'No_PGD_No_GAN_Noisy Segment ECG Model V3'. The title suggests it contains electrocardiogram (ECG) signal data, likely segmented and containing noise. Its author, organization, and temporal scope are unknown.
CNN-8h-Checkpoint is a dataset published on Kaggle. The title suggests it contains saved model weights or training states for a convolutional neural network. The specific architecture, training data, and performance metrics are unknown from the provided metadata.
BanglaVision60K is a large-scale dataset for Bengali image captioning. The dataset likely contains 60,000 images paired with descriptive Bengali text captions. Its author, organization, and last update date are unknown.
An image dataset created by the Brazilian Agricultural Research Corporation (Embrapa) for studying object detection and instance segmentation in viticulture. It provides images and annotations of five different grape varieties, capturing variance in pose, illumination, focus, and genetic and phenological traits. The dataset was created by Thiago Teixeira Santos.
Brazilian municipal civil servants were surveyed to analyze the relationship between organizational commitment and job satisfaction. The study used validated scales based on Meyer and Allen's commitment model and Siqueira's satisfaction construct. Quantitative methods included t-tests, ANOVA, factor analysis, and structural equation modeling.
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.