Multiple Objects Matting Dataset Ideal for image editing, AI driven content creation, and advanced graphics research.

Graph and download economic data for Multiple Jobholders as a Percent of Employed (LNU02026620) from Jan 1994 to May 2025 about multiple jobholders, 16 years +, percent, household survey, employment, and USA.

shahin-canary/multiple-image-label dataset hosted on Hugging Face and contributed by the HF Datasets community

This statistic shows the total number of 3 to 21 year olds with multiple disabilities in the United States who was served under the Individuals with Disabilities Education Act (IDEA) from 1990/91 to 2018/19. In 2018/19, there were approximately 133,000 persons aged 3- to 21-years-old with multiple disabilities who were covered by IDEA.

Ghana Multiple Indicator Cluster Survey 2017 / 2018

SDAT customer service improvement from multiple perspectives FY22 Customer Service Annual Report

Classification of Mars Terrain Using Multiple Data Sources Alan Kraut1, David Wettergreen1 ABSTRACT. Images of Mars are being collected faster than they can be analyzed by planetary scientists. Automatic analysis of images would enable more rapid and more consistent image interpretation and could draft geologic maps where none yet exist. In this work we develop a method for incorporating images from multiple instruments to classify Martian terrain into multiple types. Each image is segmented into contiguous groups of similar pixels, called superpixels, with an associated vector of discriminative features. We have developed and tested several classification algorithms to associate a best class to each superpixel. These classifiers are trained using three different manual classifications with between 2 and 6 classes. Automatic classification accuracies of 50 to 80% are achieved in leave-one-out cross-validation across 20 scenes using a multi-class boosting classifier.

This dataset tracks annual black student percentage from 2007 to 2023 for P.s. 37 Multiple Intelligence School vs. New York and New York City Geographic District #10 School District

The 2010-2011 Afghanistan Multiple Indicator Cluster Survey (MICS) is a nationally representative sample survey that presents data on the social, health, and educational status of women and children in Afghanistan. It was conducted in 2010-2011 by the Central Statistics Organisation (CSO) of the Government of the Islamic Republic of Afghanistan, with the technical and financial support of NICEF. The survey is based on the need to monitor progress towards goals and targets emanating from recent international agreements such as the Millennium Declaration and the Plan of Action of A World Fit For Children. It further helps track progress towards the Afghan Government s policy commitments to reduce poverty and support the wellbeing of women and children, such as the commitments made through the Afghanistan National Development Strategy (ANDS). The primary objectives of the Afghanistan MICS 2010-2011 include the following: To provide up-to-date information for assessing the situation of children and women in Afghanistan; To generate data on the situation of children and women, including the identification of vulnerable groups and of disparities. To furnish data required for monitoring progress toward goals established in the Millennium Declaration and other internationally agreed upon goals; To serve as the evidence basis for future action and programming design, and to inform relevant policies and interventions; To contribute to the improvement of data and monitoring systems in Afghanistan and to strengthen technical expertise in the design, implementation, and analysis of such systems.

DOT - Multiple Countries

According to a survey on subscription video on demand (SvoD) conducted by Rakuten Insight in June 2024, approximately 65 percent of Indonesian respondents stated that they subscribed to more than one SvoD providers because the shows they were interested in were spread across various providers. The same survey found that around 54 percent of respondents in Indonesia subscribed to SvoD services.

JA-Multi-Image-VQA

  Dataset Description

JA-Multi-Image-VQA is a dataset for evaluating the question answering capabilities on multiple image inputs. We carefully collected a diverse set of 39 images with 55 questions in total. Some images contain Japanese culture and objects in Japan. The Japanese questions and answers were created manually.

  Usage

from datasets import load_dataset dataset = load_dataset("SakanaAI/JA-Multi-Image-VQA", split="test")… See the full description on the dataset page: https://huggingface.co/datasets/SakanaAI/JA-Multi-Image-VQA.

This dataset tracks annual asian student percentage from 2006 to 2022 for P.s. 37 Multiple Intelligence School vs. New York and New York City Geographic District #10 School District

This study seek to address the following 5 main questions:

(1) Where are the preferred target species located and what spatial models serve as the best predictors of species abundance; (2) Where in Kubulau is current fishing effort focused and how does it vary by gear; (3) What are the differences in opportunity costs across users of different fishing gear, based on current and potential costs; (4) Where would be the best areas to modify the current MPA network to reduce conflict and improve fisheries benefits and which users would be most affected by these changes; and (5) How can this model be applied to other resource management decisions?

multiple files making up a huge dataset

These data sets were originally created for the following publications:

M. E. Houle, H.-P. Kriegel, P. Kröger, E. Schubert, A. Zimek Can Shared-Neighbor Distances Defeat the Curse of Dimensionality? In Proceedings of the 22nd International Conference on Scientific and Statistical Database Management (SSDBM), Heidelberg, Germany, 2010.

H.-P. Kriegel, E. Schubert, A. Zimek Evaluation of Multiple Clustering Solutions In 2nd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings Held in Conjunction with ECML PKDD 2011, Athens, Greece, 2011.

The outlier data set versions were introduced in:

E. Schubert, R. Wojdanowski, A. Zimek, H.-P. Kriegel On Evaluation of Outlier Rankings and Outlier Scores In Proceedings of the 12th SIAM International Conference on Data Mining (SDM), Anaheim, CA, 2012.

They are derived from the original image data available at https://aloi.science.uva.nl/

The image acquisition process is documented in the original ALOI work: J. M. Geusebroek, G. J. Burghouts, and A. W. M. Smeulders, The Amsterdam library of object images, Int. J. Comput. Vision, 61(1), 103-112, January, 2005

Additional information is available at: https://elki-project.github.io/datasets/multi_view

The following views are currently available:

    Feature type
    Description
    Files


    Object number
    Sparse 1000 dimensional vectors that give the true object assignment
    objs.arff.gz


    RGB color histograms
    Standard RGB color histograms (uniform binning)
    aloi-8d.csv.gz aloi-27d.csv.gz aloi-64d.csv.gz aloi-125d.csv.gz aloi-216d.csv.gz aloi-343d.csv.gz aloi-512d.csv.gz aloi-729d.csv.gz aloi-1000d.csv.gz


    HSV color histograms
    Standard HSV/HSB color histograms in various binnings
    aloi-hsb-2x2x2.csv.gz aloi-hsb-3x3x3.csv.gz aloi-hsb-4x4x4.csv.gz aloi-hsb-5x5x5.csv.gz aloi-hsb-6x6x6.csv.gz aloi-hsb-7x7x7.csv.gz aloi-hsb-7x2x2.csv.gz aloi-hsb-7x3x3.csv.gz aloi-hsb-14x3x3.csv.gz aloi-hsb-8x4x4.csv.gz aloi-hsb-9x5x5.csv.gz aloi-hsb-13x4x4.csv.gz aloi-hsb-14x5x5.csv.gz aloi-hsb-10x6x6.csv.gz aloi-hsb-14x6x6.csv.gz


    Color similiarity
    Average similarity to 77 reference colors (not histograms) 18 colors x 2 sat x 2 bri + 5 grey values (incl. white, black)
    aloi-colorsim77.arff.gz (feature subsets are meaningful here, as these features are computed independently of each other)


    Haralick features
    First 13 Haralick features (radius 1 pixel)
    aloi-haralick-1.csv.gz


    Front to back
    Vectors representing front face vs. back faces of individual objects
    front.arff.gz


    Basic light
    Vectors indicating basic light situations
    light.arff.gz


    Manual annotations
    Manually annotated object groups of semantically related objects such as cups
    manual1.arff.gz

Outlier Detection Versions

Additionally, we generated a number of subsets for outlier detection:

    Feature type
    Description
    Files


    RGB Histograms
    Downsampled to 100000 objects (553 outliers)
    aloi-27d-100000-max10-tot553.csv.gz aloi-64d-100000-max10-tot553.csv.gz



    Downsampled to 75000 objects (717 outliers)
    aloi-27d-75000-max4-tot717.csv.gz aloi-64d-75000-max4-tot717.csv.gz



    Downsampled to 50000 objects (1508 outliers)
    aloi-27d-50000-max5-tot1508.csv.gz aloi-64d-50000-max5-tot1508.csv.gz

The 2000 Albania Multiple Indicator Cluster Survey (MICS) is a nationally representative survey of households, women, and children. The main objectives of the survey are to provide for the first time information for assessing the situation of children and women in Albania at the end of the decade and to furnish data needed for monitoring progress toward goals established at the World Summit for Children and as a basis for future action. The 2000 Albania Multiple Indicator Cluster Survey has as its primary objectives: To provide up-to-date information for assessing the situation of children and women in Albania at the end of the decade in order to develop effective policies and strategies over the next decade; To furnish data on the situation of children needed for the compilation of the initial and second CRC country reports; To measure Albania’s performance vis a vis the 1990 World Summit for Children goals. To provide analysis of the situation of children for inclusion in deliberations at the United Nations Special Session on children as a basis for future action. To contribute to the improvement of data and monitoring systems in Albania and to strengthen technical expertise in design, implementation, and analysis of such systems.

Multiple different relationship types between two variables.

Income Statement: Multiple Banks: Income: Caused Interests: Obligations with the Public data was reported at 0.349 USD mn in Jul 2019. This records an increase from the previous number of 0.295 USD mn for Jun 2019. Income Statement: Multiple Banks: Income: Caused Interests: Obligations with the Public data is updated monthly, averaging 0.191 USD mn from Jan 2019 (Median) to Jul 2019, with 7 observations. The data reached an all-time high of 0.349 USD mn in Jul 2019 and a record low of 0.047 USD mn in Jan 2019. Income Statement: Multiple Banks: Income: Caused Interests: Obligations with the Public data remains active status in CEIC and is reported by Superintendence of Banks. The data is categorized under Global Database’s Ecuador – Table EC.KB012: Income Statement: Superintendence of Banks: Multiple Banks.

This dataset present information on the age-sex specific incidence rate of multiple sclerosis for Alberta Health Service (AHS) and five AHS Continuum zones expressed as per 100,000 population and as a percentage.