People Counter Top View

## Overview

People Counter Top View is a dataset for object detection tasks - it contains Person annotations for 200 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This statistic illustrates the share of opinions on divisions between people with different views compared to 20 years ago in 2019, by country. According to data from IPSOS, 57 percent of Swedish respondents said that society is more dangerous than it was 20 years ago due to the divisions between those with differing political views. This is compared to 57 percent of Americans and 53 percent of South Africans who said the same.

Top View People

## Overview

Top View People is a dataset for object detection tasks - it contains People annotations for 612 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Top View Trained

## Overview

Top View Trained is a dataset for object detection tasks - it contains People annotations for 2,743 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

In an opinion poll conducted between October and November 2024, over 24 percent of respondents in Japan stated that government policies reflect the opinion of the people at least to some extent. Around 21.5 percent thought that the ideas and views of the people are mostly not reflected by the government's policies.

This statistic depicts the results of a survey asking individuals about their opinion on social media platforms such as Facebook and Twitter giving people a voice in debates in Japan in 2018. According to data provided by Ipsos, around 26 percent of respondents agreed that social media were giving a voice to people who normally would not participate in debates and social issues.

According to an opinion poll conducted between October and November 2024, older age cohorts were most satisfied with government policies in Japan. Over 39 percent of respondents aged 70 and above stated that government policies reflect the opinion of the people at least to some extent. The share of 18 to 29-year-olds who were of the same opinion was around 18 percent.

Dataset

This dataset was created by Michael W. Kearney

Contents

Human Detection Top View

## Overview

Human Detection Top View is a dataset for object detection tasks - it contains Person annotations for 3,829 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Small Object Aerial Person Detection Dataset:

The aerial dataset publication comprises a collection of frames captured from unmanned aerial vehicles (UAVs) during flights over the University of Cyprus campus and Civil Defense exercises. The dataset is primarily intended for people detection, with a focus on detecting small objects due to the top-view perspective of the images. The dataset includes annotations generated in popular formats such as YOLO, COCO, and VOC, making it highly versatile and accessible for a wide range of applications. Overall, this aerial dataset publication represents a valuable resource for researchers and practitioners working in the field of computer vision and machine learning, particularly those focused on people detection and related applications.

It is advised to further enhance the dataset so that random augmentations are probabilistically applied to each image prior to adding it to the batch for training. Specifically, there are a number of possible transformations such as geometric (rotations, translations, horizontal axis mirroring, cropping, and zooming), as well as image manipulations (illumination changes, color shifting, blurring, sharpening, and shadowing).

This OIG website contains a list of recently issued advisory opinions and a link to archives of previously issued advisory opinions. In accordance with section 1128D (b) (5) (A) (v) of the Social Security Act and 42 CFR 1008.47 of the Office of Inspector General's (OIG) regulations, advisory opinions issued by the OIG are made available to the general public through this OIG website. One purpose of the advisory opinion process is to provide meaningful advice on the application of the anti-kickback statute and other OIG sanction statutes in specific factual situations. Please note, however, that advisory opinions are binding and may legally be relied upon only by the requestor. Because each opinion will apply legal standards to a set of facts involving certain known persons who provide specific statements about key factual issues, no third parties are bound nor may they legally rely on these advisory opinions.

The survey was conducted by Central Research Services on behalf of Japan's Prime Minister's office. A National sample of 16,739 adults were interviewed in January 1969. The survey was commissioned by the Prime Minister's office to seek opinions on living conditions and requests sent to the government.

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at the Roper Center for Public Opinion Research at https://doi.org/10.25940/ROPER-31071960. We highly recommend using the Roper Center version as they may make this dataset available in multiple data formats in the future.

This dataset is a statistical table of public satisfaction with opinions reflected in the year 106.

According to a survey conducted on environmental issues in Japan in October 2020, amounting to 588 answers, the majority of respondents stated that they thought that environmental issues were caused by activities of humans. Only a small amount of respondents mentioned that they did not think so.

Introduction

In 2013, students of the Statistics class at "https://fses.uniba.sk/en/">FSEV UK were asked to invite their friends to participate in this survey.

• The data file (responses.csv) consists of 1010 rows and 150 columns (139 integer and 11 categorical).
• For convenience, the original variable names were shortened in the data file. See the columns.csv file if you want to match the data with the original names.
• The data contain missing values.
• The survey was presented to participants in both electronic and written form.
• The original questionnaire was in Slovak language and was later translated into English.
• All participants were of Slovakian nationality, aged between 15-30.

The variables can be split into the following groups:

• Music preferences (19 items)
• Movie preferences (12 items)
• Hobbies & interests (32 items)
• Phobias (10 items)
• Health habits (3 items)
• Personality traits, views on life, & opinions (57 items)
• Spending habits (7 items)
• Demographics (10 items)

Research questions

Many different techniques can be used to answer many questions, e.g.

• Clustering: Given the music preferences, do people make up any clusters of similar behavior?
• Hypothesis testing: Do women fear certain phenomena significantly more than men? Do the left handed people have different interests than right handed?
• Predictive modeling: Can we predict spending habits of a person from his/her interests and movie or music preferences?
• Dimension reduction: Can we describe a large number of human interests by a smaller number of latent concepts?
• Correlation analysis: Are there any connections between music and movie preferences?
• Visualization: How to effectively visualize a lot of variables in order to gain some meaningful insights from the data?
• (Multivariate) Outlier detection: Small number of participants often cheats and randomly answers the questions. Can you identify them? Hint: [Local outlier factor][1] may help.
• Missing values analysis: Are there any patterns in missing responses? What is the optimal way of imputing the values in surveys?
• Recommendations: If some of user's interests are known, can we predict the other? Or, if we know what a person listen, can we predict which kind of movies he/she might like?

Past research

• (in slovak) Sleziak, P. - Sabo, M.: Gender differences in the prevalence of specific phobias. Forum Statisticum Slovacum. 2014, Vol. 10, No. 6. [Differences (gender + whether people lived in village/town) in the prevalence of phobias.]

• Sabo, Miroslav. Multivariate Statistical Methods with Applications. Diss. Slovak University of Technology in Bratislava, 2014. [Clustering of variables (music preferences, movie preferences, phobias) + Clustering of people w.r.t. their interests.]

Questionnaire

MUSIC PREFERENCES

1. I enjoy listening to music.: Strongly disagree 1-2-3-4-5 Strongly agree (integer)
2. I prefer.: Slow paced music 1-2-3-4-5 Fast paced music (integer)
3. Dance, Disco, Funk: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
4. Folk music: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
5. Country: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
6. Classical: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
7. Musicals: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
8. Pop: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
9. Rock: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
10. Metal, Hard rock: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
11. Punk: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
12. Hip hop, Rap: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
13. Reggae, Ska: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
14. Swing, Jazz: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
15. Rock n Roll: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
16. Alternative music: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
17. Latin: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
18. Techno, Trance: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
19. Opera: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)

MOVIE PREFERENCES

1. I really enjoy watching movies.: Strongly disagree 1-2-3-4-5 Strongly agree (integer)
2. Horror movies: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
3. Thriller movies: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
4. Comedies: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
5. Romantic movies: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
6. Sci-fi movies: Don't enjoy at all 1-2-3-4-5 Enjoy very much (integer)
7. War movies: Don't enjoy at all 1-2-3-4-5 E...

Scholars often assert that public support for judicial authority induces Congress to grant resources and discretion to the Supreme Court. However, the theory of competing public agency embraced by the Constitution suggests that public support for courts cannot, by itself, explain congressional support for judicial authority. Instead, the logic of the separation of powers system indicates that legislative support for the institutional capacity of courts will be a function of public confidence in the legislature as well as evaluations of the judiciary. We test this theory, finding that public confidence in both Congress and the Court significantly affect congressional support for the Supreme Court, controlling for the ideological distance between the Court and Congress as well as the Court's workload. The results offer a more refined and complex view of the role of public sentiment in balancing institutional power in American politics.

Existing literature on foreign aid and human rights often presupposes that constituents favor using foreign policy to promote human rights abroad and, in turn, lead elected policymakers to pursue such policies to retain electoral support. This assumption, although frequently asserted, has not been empirically evaluated. And there are reasons to be skeptical about how much public opinion supports human rights foreign policy in comparison to other policy objectives. This paper explores US public opinion about human rights, by asking two questions: does the public think human rights should be a factor in foreign aid decisions and does the context – for instance, the strategic or economic relationship between the donor country and potential recipient – affect this? This paper uses results from a nationwide experimental survey to parse out these questions: do respondents favor a punitive response to human rights abuses? Does it matter if U.S. economic or strategic interests are at stake? I find that the majority of respondents support cutting foreign aid to punish human rights violators and that this preference depends only minimally on the importance of the recipient. This paper contributes to existing scholarship by testing a key micro-foundation of the literature on human rights and foreign policy.

This annual survey, fielded August to October 1999, was conducted in over 50 countries to solicit public opinion on social and political issues. Respondents were asked to give their opinion on the environment. Questions included the overall state that the environment is in, if the government has done too much, too little, or just the right amount concerning the environment, and the biggest threat to the environment for future generations. They were also queried on whether they thought their countries elections were free and fair, and what words best describe their perception of the government. Questions concerning religion were also asked. These focused on whether there is only one true religion, many true religions, or no essential truth in any religion, how important God is in their life, and praying and meditation. Respondents were asked to give their opinion on women's rights. Questions included whether they thought women have equal rights in their country, whether they thought education is more important for boys or girls, whether women need to have children in order to feel fulfilled, and whether women in advanced countries must insist more for the rights of women in the developing world. They were also asked to give their opinion on the issue of crime. They were asked how concerned they were about the level of crime in their country, if crime had increased or decreased in the last five years, how well the government was handling crime, and if they were for or against the death penalty. They were also asked what they thought matters most in life, and what they thought about the United Nations. Questions pertaining to human rights were also asked, such as whether discrimination based on sex, color, language, religion, or political opinion was taking place in their country. They were also asked if they thought that the use of torture was being documented, how effective stricter international laws would be in reducing torture, how effective more prosecutions of those suspected of torture would be in eliminating it, how effective greater public awareness of the incidence of torture would be in helping eliminate it, and how effective a grassroots campaign to eliminate torture would be. Respondents were also queried on the year 2000 computer problem. Demographics include sex, age, education, occupation, marital status, children under 15 living in household, religious denomination, religiosity, and region.

According to a survey conducted in 2024, 42 percent of Americans thought that society has gone too far in accepting people who are transgender in the United States. 46 percent of white Americans and 41 percent of Hispanic Americans also shared this belief, compared to only 26 percent of Black Americans.

Human Detection Aerial View

## Overview

Human Detection Aerial View is a dataset for object detection tasks - it contains Humans annotations for 2,644 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).