This graph shows the population of the U.S. by race and ethnic group from 2000 to 2023. In 2023, there were around 21.39 million people of Asian origin living in the United States. A ranking of the most spoken languages across the world can be accessed here. U.S. populationCurrently, the white population makes up the vast majority of the United States’ population, accounting for some 252.07 million people in 2023. This ethnicity group contributes to the highest share of the population in every region, but is especially noticeable in the Midwestern region. The Black or African American resident population totaled 45.76 million people in the same year. The overall population in the United States is expected to increase annually from 2022, with the 320.92 million people in 2015 expected to rise to 341.69 million people by 2027. Thus, population densities have also increased, totaling 36.3 inhabitants per square kilometer as of 2021. Despite being one of the most populous countries in the world, following China and India, the United States is not even among the top 150 most densely populated countries due to its large land mass. Monaco is the most densely populated country in the world and has a population density of 24,621.5 inhabitants per square kilometer as of 2021. As population numbers in the U.S. continues to grow, the Hispanic population has also seen a similar trend from 35.7 million inhabitants in the country in 2000 to some 62.65 million inhabitants in 2021. This growing population group is a significant source of population growth in the country due to both high immigration and birth rates. The United States is one of the most racially diverse countries in the world.

Among the 81 largest metropolitan areas (by population) in the United States, Knoxville, Tennessee was ranked first with **** percent of residents reporting as white, non-Hispanic in 2023.

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Hill Country Village by race. It includes the distribution of the Non-Hispanic population of Hill Country Village across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Hill Country Village across relevant racial categories.

Key observations

Of the Non-Hispanic population in Hill Country Village, the largest racial group is White alone with a population of 584 (76.74% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Hill Country Village
• Population: The population of the racial category (for Non-Hispanic) in the Hill Country Village is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Hill Country Village total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Hill Country Village Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Country Club by race. It includes the distribution of the Non-Hispanic population of Country Club across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Country Club across relevant racial categories.

Key observations

Of the Non-Hispanic population in Country Club, the largest racial group is White alone with a population of 2,707 (92.20% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Country Club
• Population: The population of the racial category (for Non-Hispanic) in the Country Club is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Country Club total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Country Club Population by Race & Ethnicity. You can refer the same here

Diversity in Tech Statistics: In today's tech-driven world, discussions about diversity in the technology sector have gained significant traction. Recent statistics shed light on the disparities and opportunities within this industry. According to data from various sources, including reports from leading tech companies and diversity advocacy groups, the lack of diversity remains a prominent issue. For example, studies reveal that only 25% of computing jobs in the United States are held by women, while Black and Hispanic individuals make up just 9% of the tech workforce combined. Additionally, research indicates that LGBTQ+ individuals are underrepresented in tech, with only 2.3% of tech workers identifying as LGBTQ+. Despite these challenges, there are promising signs of progress. Companies are increasingly recognizing the importance of diversity and inclusion initiatives, with some allocating significant resources to address these issues. For instance, tech giants like Google and Microsoft have committed millions of USD to diversity programs aimed at recruiting and retaining underrepresented talent. As discussions surrounding diversity in tech continue to evolve, understanding the statistical landscape is crucial in fostering meaningful change and creating a more inclusive industry for all. Editor’s Choice In 2021, 7.9% of the US labor force was employed in technology. Women hold only 26.7% of tech employment, while men hold 73.3% of these positions. White Americans hold 62.5% of the positions in the US tech sector. Asian Americans account for 20% of jobs, Latinx Americans 8%, and Black Americans 7%. 83.3% of tech executives in the US are white. Black Americans comprised 14% of the population in 2019 but held only 7% of tech employment. For the same position, at the same business, and with the same experience, women in tech are typically paid 3% less than men. The high-tech sector employs more men (64% against 52%), Asian Americans (14% compared to 5.8%), and white people (68.5% versus 63.5%) compared to other industries. The tech industry is urged to prioritize inclusion when hiring, mentoring, and retaining employees to bridge the digital skills gap. Black professionals only account for 4% of all tech workers despite being 13% of the US workforce. Hispanic professionals hold just 8% of all STEM jobs despite being 17% of the national workforce. Only 22% of workers in tech are ethnic minorities. Gender diversity in tech is low, with just 26% of jobs in computer-related sectors occupied by women. Companies with diverse teams have higher profitability, with those in the top quartile for gender diversity being 25% more likely to have above-average profitability. Every month, the tech industry adds about 9,600 jobs to the U.S. economy. Between May 2009 and May 2015, over 800,000 net STEM jobs were added to the U.S. economy. STEM jobs are expected to grow by another 8.9% between 2015 and 2024. The percentage of black and Hispanic employees at major tech companies is very low, making up just one to three percent of the tech workforce. Tech hiring relies heavily on poaching and incentives, creating an unsustainable ecosystem ripe for disruption. Recruiters have a significant role in disrupting the hiring process to support diversity and inclusion. You May Also Like To Read Outsourcing Statistics Digital Transformation Statistics Internet of Things Statistics Computer Vision Statistics

In the fiscal year of 2019, 21.39 percent of active-duty enlisted women were of Hispanic origin. The total number of active duty military personnel in 2019 amounted to 1.3 million people.

Ethnicities in the United States The United States is known around the world for the diversity of its population. The Census recognizes six different racial and ethnic categories: White American, Native American and Alaska Native, Asian American, Black or African American, Native Hawaiian and Other Pacific Islander. People of Hispanic or Latino origin are classified as a racially diverse ethnicity.

The largest part of the population, about 61.3 percent, is composed of White Americans. The largest minority in the country are Hispanics with a share of 17.8 percent of the population, followed by Black or African Americans with 13.3 percent. Life in the U.S. and ethnicity However, life in the United States seems to be rather different depending on the race or ethnicity that you belong to. For instance: In 2019, native Hawaiians and other Pacific Islanders had the highest birth rate of 58 per 1,000 women, while the birth rae of white alone, non Hispanic women was 49 children per 1,000 women.

The Black population living in the United States has the highest poverty rate with of all Census races and ethnicities in the United States. About 19.5 percent of the Black population was living with an income lower than the 2020 poverty threshold. The Asian population has the smallest poverty rate in the United States, with about 8.1 percent living in poverty.

The median annual family income in the United States in 2020 earned by Black families was about 57,476 U.S. dollars, while the average family income earned by the Asian population was about 109,448 U.S. dollars. This is more than 25,000 U.S. dollars higher than the U.S. average family income, which was 84,008 U.S. dollars.

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Country Club Heights by race. It includes the distribution of the Non-Hispanic population of Country Club Heights across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Country Club Heights across relevant racial categories.

Key observations

Of the Non-Hispanic population in Country Club Heights, the largest racial group is White alone with a population of 169 (88.95% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Country Club Heights
• Population: The population of the racial category (for Non-Hispanic) in the Country Club Heights is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Country Club Heights total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Country Club Heights Population by Race & Ethnicity. You can refer the same here

This dataset offers documentary evidence of racism for 15 countries (top performing democracies in the 2022-23 period). This is done to demonstrate the prevalence of racism as a chronic problem for, and with recent presentations in, the world’s high performing democracies. Accounts of racism are divided into the following categories of document types: (1) Academic research, (2) Government body reports, (3) Non-government body reports, (4) journalistic reports, and (5) non-academic polling/opinion surveys, to ensure a diversity of evidentiary claims per county.

Up to 10 accounts have been provided for each category, as this was the upward limit of our Research Assistance funding. In no case is this an exhaustive listing even though, for some categories (such as government reports from Costa Rica) we did not reach 10 accounts. Further research with new funding is required to build on this work.

The data is provided alphabetically per country in tables.

Attribution: Jean-Paul Gagnon, Seema Shah, and Blake Kelly. 2025. "15 High-Performance Democracies with documented accounts of Racism per Country". V1. [DOI or hyperlink to Mendeley page]

Associated publication: Jean-Paul Gagnon, Seema Shah, Blake Kelly. 2025. "Racism Undermines High Performance Democracies". Chinese Political Science Review. Forthcoming. Abstract below.

Racism Undermines High-Performance Democracies

Abstract. Racism is a chronic problem for fifteen of the world’s top scoring democracies (Denmark serves as a case study). This evidence – which we draw from academic research, government and non-government body reports, journalistic reports, and polling data published between 2013 and 2023 – troubles doctrines of representative, liberal, electoral, and participatory theories of democracy. In this article, we apply an aspect of Graefrath and Jahn’s ontological coherence rule – this being a comparison of the ontic commitments required by each theory against ontic commitments of racism as defined by the Australian Human Rights Commission – to conceptually demonstrate this claim. This leads us to the conclusion that real-existing democracies experiencing racism are also likely experiencing a constraint on their democratic capacities. Racism, in short, undermines at least four types of democracy. We end our analysis with a suggestion to adapt International IDEA’s 2024 PODS methodology so that it may capture and contrast the opinions of racialized minorities, alongside the opinions of experts, the statistically average person, and other marginalized persons, as the next step in this line of research.

Keywords. Democracy, Racism, Liberalism, Elections, Representation, Participation.

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Country Life Acres by race. It includes the distribution of the Non-Hispanic population of Country Life Acres across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Country Life Acres across relevant racial categories.

Key observations

Of the Non-Hispanic population in Country Life Acres, the largest racial group is White alone with a population of 74 (96.10% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Country Life Acres
• Population: The population of the racial category (for Non-Hispanic) in the Country Life Acres is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Country Life Acres total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Country Life Acres Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Town And Country by race. It includes the distribution of the Non-Hispanic population of Town And Country across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Town And Country across relevant racial categories.

Key observations

Of the Non-Hispanic population in Town And Country, the largest racial group is White alone with a population of 9,320 (82.32% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Town And Country
• Population: The population of the racial category (for Non-Hispanic) in the Town And Country is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Town And Country total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Town And Country Population by Race & Ethnicity. You can refer the same here

Introduction

Welcome to the Caucasian Child Faces Dataset, meticulously curated to enhance face recognition models and support the development of advanced biometric identification systems, child identification models, and other facial recognition technologies.

Facial Image Data

This dataset comprises over 3,000 child image sets, divided into participant-wise sets with each set including:

Diversity and Representation

The dataset includes contributions from a diverse network of children across Caucasian countries:

Quality and Conditions

To ensure high utility and robustness, all images are captured under varying conditions:

Metadata

Each facial image set is accompanied by detailed metadata for each participant, including:

This metadata is essential for training models that can accurately recognize and identify children's faces across different demographics and conditions.

Usage and Applications

This facial image dataset is ideal for various applications in the field of computer vision, including but not limited to:

Secure and Ethical Collection

Updates and

THE POLL

As part of Cards Against Humanity Saves America, this poll is funded for one year of monthly public opinion polls. Cards Against Humanity is asking the American people about their social and political views, what they think of the president, and their pee-pee habits.

To conduct their polls in a scientifically rigorous manner, they partnered with Survey Sampling International — a professional research firm — to contact a nationally representative sample of the American public. For the first three polls, they interrupted people’s dinners on both their cell phones and landlines, and a total of about 3,000 adults didn’t hang up immediately. They examined the data for statistically significant correlations which can be found here: [https://thepulseofthenation.com/][1]

Content

• Polls are released each month (they are still polling so this will be updated each month)
  
• Row one is the header and contains the questions
  
• Each row is one respondent's answers
  

Questions in the Sep 2017 poll:

• Income
• Gender
• Age
• Age Range
• Political Affiliation
• Do you approve or disapprove of how Donald Trump is handling his job as president?
• What is your highest level of education?
• What is your race?
• What is your marital status?
• What would you say is the likelihood that your current job will be entirely performed by robots or computers within the next decade?
• Do you believe that climate change is real and caused by people, real but not caused by people, or not real at all?"
• How many Transformers movies have you seen?
• Do you agree or disagree with the following statement: scientists are generally honest and are serving the public good.
• Do you agree or disagree with the following statement: vaccines are safe and protect children from disease.
• "How many books, if any have you read in the past year?"
• Do you believe in ghosts?
• What percentage of the federal budget would you estimate is spent on scientific research?
• "Is federal funding of scientific research too high too low or about right?"
• True or false: the earth is always farther away from the sun in the winter than in the summer.
• "If you had to choose: would you rather be smart and sad or dumb and happy?"
• Do you think it is acceptable or unacceptable to urinate in the shower?

Questions from Oct 2017 poll

• Income
• Gender
• Age
• Age Range
• Political Affiliation
• Do you approve or disapprove of how Donald Trump is handling his job as president?
• What is your highest level of education?
• What is your race?
• From what you have heard or seen do you mostly agree or mostly disagree with the beliefs of White Nationalists?
• If you had to guess what percentage of Republicans would say that they mostly agree with the beliefs of White Nationalists?
• Would you say that you love America?
• If you had to guess, what percentage of Democrats would say that they love America?
• Do you think that government policies should help those who are poor and struggling in America?
• If you had to guess, what percentage of Republicans would say yes to that question?
• Do you think that most white people in America are racist?
• If you had to guess, what percentage of Democrats would say yes to that question?
• Have you lost any friendships or other relationships as a result of the 2016 presidential election?
• Do you think it is likely or unlikely that there will be a Civil War in the United States within the next decade?
• Have you ever gone hunting?
• Have you ever eaten a kale salad?
• If Dwayne "The Rock" Johnson ran for president as a candidate for your political party, would you vote for him?
• Who would you prefer as president of the United States, Darth Vader or Donald Trump?

Questions from Nov 2017 poll

• Income
• Gender
• Age
• Age Range
• In politics today, do you consider yourself a Democrat, a Republican or Independent?
• Would you say you are liberal, conservative, or moderate?
• What is your highest level of education? (High school or less, Some college, College degree, Graduate degree)
• What is your race? (white, black, latino, asian, other)
• Do you live in a city, suburb, or small town?
• Do you approve, disapprove, or neither approve nor disapprove of how Donald Trump is handling his job as president?
• Do you think federal funding for welfare programs in America should be increased, decreased, or kept the same?
• Do you think poor black people are more likely to benefit from welfare programs than poor white people?
• Do you think poor people in cities are more likely to benefit from welfare programs than poor people in small towns?
• If you had to choose, would you rather live in a more equal society or a more unequal society?

Acknowledgements

These polls are from Cards Against Humanity Saves America and the raw data can be found here: [https://thepulse...

South Africa Population: 15 to 64 Years: White data was reported at 2,978.591 Person th in Sep 2018. This records a decrease from the previous number of 2,987.055 Person th for Jun 2018. South Africa Population: 15 to 64 Years: White data is updated quarterly, averaging 3,143.298 Person th from Mar 2008 (Median) to Sep 2018, with 43 observations. The data reached an all-time high of 3,277.317 Person th in Mar 2008 and a record low of 2,978.591 Person th in Sep 2018. South Africa Population: 15 to 64 Years: White data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.G001: Population.

This map shows the predominant race of mothers who have given birth between the ages of 15-19. This is shown by county, state, and country from the 2022 County Health Rankings. The data comes from the County Health Rankings 2022 layer. The County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. "By ranking the health of nearly every county in the nation, County Health Rankings & Roadmaps (CHR&R) illustrates how where we live affects how well and how long we live. CHR&R also shows what each of us can do to create healthier places to live, learn, work, and play – for everyone."Counties are ranked within their state on both health outcomes and health factors. Counties with a lower (better) health outcomes ranking than health factors ranking may see the health of their county decline in the future, as factors today can result in outcomes later. Conversely, counties with a lower (better) factors ranking than outcomes ranking may see the health of their county improve in the future.

In 2023, **** percent of Black people living in the United States were living below the poverty line, compared to *** percent of white people. That year, the total poverty rate in the U.S. across all races and ethnicities was **** percent. Poverty in the United States Single people in the United States making less than ****** U.S. dollars a year and families of four making less than ****** U.S. dollars a year are considered to be below the poverty line. Women and children are more likely to suffer from poverty, due to women staying home more often than men to take care of children, and women suffering from the gender wage gap. Not only are women and children more likely to be affected, racial minorities are as well due to the discrimination they face. Poverty data Despite being one of the wealthiest nations in the world, the United States had the third highest poverty rate out of all OECD countries in 2019. However, the United States' poverty rate has been fluctuating since 1990, but has been decreasing since 2014. The average median household income in the U.S. has remained somewhat consistent since 1990, but has recently increased since 2014 until a slight decrease in 2020, potentially due to the pandemic. The state that had the highest number of people living below the poverty line in 2020 was California.

Introduction

Welcome to the Caucasian Human Face with Occlusion Dataset, carefully curated to support the development of robust facial recognition systems, occlusion detection models, biometric identification technologies, and KYC verification tools. This dataset provides real-world variability by including facial images with common occlusions, helping AI models perform reliably under challenging conditions.

Facial Image Data

The dataset comprises over 3,000 high-quality facial images, organized into participant-wise sets. Each set includes:

Diversity & Representation

Image Quality & Capture Conditions

To ensure robustness and real-world utility, images were captured under diverse conditions:

Metadata

Each image is paired with detailed metadata to enable advanced filtering, model tuning, and analysis:

This rich metadata helps train models that can recognize faces even when partially obscured.

Use Cases & Applications

This dataset is ideal for a wide range of real-world and research-focused applications, including:

Secure & Ethical Collection

Dataset Updates &

Introduction

Welcome to the Caucasian Facial Expression Image Dataset, curated to support the development of advanced facial expression recognition systems, biometric identification models, KYC verification processes, and a wide range of facial analysis applications. This dataset is ideal for training robust emotion-aware AI solutions.

Facial Expression Data

The dataset includes over 1000 high-quality facial expression images, grouped into participant-wise sets. Each participant contributes:

Diversity & Representation

Image Quality & Capture Conditions

To ensure generalizability and robustness in model training, images were captured under varied real-world conditions:

Metadata

Each participant's image set is accompanied by detailed metadata, enabling precise filtering and training:

This metadata helps in building expression recognition models that are both accurate and inclusive.

Use Cases & Applications

This dataset is ideal for a variety of AI and computer vision applications, including:

Secure & Ethical Collection

Dataset Updates & Customization

To support evolving AI development needs, this dataset is regularly updated and can be tailored to project-specific requirements. Custom options include:

In 2023, according to the most recent national data, approximately 46 percent of people living in Brazil identified as Pardo Brazilian, making it the largest ethnic group in the country. In 2012, whites were the largest group, accounting for 46 percent of the population.

Ecuador Population: White data was reported at 232,431.718 Person in Jun 2019. This records an increase from the previous number of 191,776.444 Person for Mar 2019. Ecuador Population: White data is updated quarterly, averaging 240,546.133 Person from Dec 2013 (Median) to Jun 2019, with 23 observations. The data reached an all-time high of 321,622.943 Person in Dec 2013 and a record low of 160,999.228 Person in Dec 2018. Ecuador Population: White data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Ecuador – Table EC.G007: ENEMDU: Population.

Abstract What kind of information can the portraits of the Andarahy, Carioca, and Mangueira clubs offer about the visual culture of Rio de Janeiro in the early 20th century and the transition from amateur to professional soccer? In contrast to images from the aristocratic team of the Fluminense Soccer Club, the portraits of the black players of these popular clubs reveal disputes for visibility in the sports field and in the urban space since the end of the 1910s. They also reveal the role of the photographic market in the co-production of signs capable of composing a new visuality for the black population. To that extent, the socio-cultural transformations of that period were more significant than is usually recognized by representing the protagonism of the black population in the negotiations around social visibility in the country’s capital.