Icon Detection With Picture Background

## Overview

Icon Detection With Picture Background is a dataset for object detection tasks - it contains Icon annotations for 313 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).

Colour icons for some common NZ garden birds with background circles (pale blue for native species; pale turquoise for introduced species). Designed by Fabiola C. Rodriguez Estrada (http://wl-links.com.mx/) for the NZ Garden Bird Survey as part of the 'Building Trustworthy Biodiversity Indicators' project funded by the Ministry for Business, Innovation and Employment.

Grey icons for some common NZ garden birds with background circles (dark grey for native species; light grey for introduced species). Designed by Fabiola C. Rodriguez Estrada (http://wl-links.com.mx/) for the NZ Garden Bird Survey as part of the 'Building Trustworthy Biodiversity Indicators' project funded by the Ministry for Business, Innovation and Employment.

MIGHTI samples the O2 A band spectral region at five different wavelengths in order to both measure the shape of the band and to specify a background radiance that is subtracted from the signal. The wavelengths of the filter passbands are selected to maximize the sensitivity to lower thermospheric temperature variations. The temperature measurement is accomplished by a multichannel photometric measurement of the spectral shape of the molecular oxygen A-band around 762 nm wavelength. For each field of view, the signals of the two oxygen lines and the A-band are detected on different regions of a single, cooled, frame transfer charge coupled device (CCD) detector. Two filter channels sample either end of the band to define a background (754.1 nm and 780.1 nm) and three more sample its shape (760.0 nm, 762.8 nm and 765.2 nm). Using three filters that sample the band shape allows the simultaneous retrieval of the atmospheric temperature and common shifts in the center wavelengths of the pass bands due to thermal drifts of the filters. On-board calibration sources are used to periodically quantify thermal drifts, simultaneously with observing the atmosphere.

In work package 6 of the nextGEMS project, several ocean-only model runs were performed with FESOM (Version 2.0) and ICON-O (Version 2.6.6), to test the sensitivity of the upper tropical Atlantic to different settings of the vertical mixing scheme. Two different mixing schemes were tested: TKE and KPP. For TKE, we tested different settings of the c_k parameter (0.1, 0.2 and 0.3), and for KPP different settings of the critical bulk Richardson number (0.3 and 0.27). These runs were done with both ICON-O and FESOM, to enable a comparison of the effects of the vertical mixing settings across different models. From ICON-O only, there are some additional TKE runs available, where we increased the interior ocean background mixing, and switched on the Langmuir turbulence parameterisation. There is also an ICON-O run which uses the FESOM default forcing bulk formulae, to check how much of the differences between the models originates from their different default bulk formulae. All model runs are ocean only, forced with hourly ERA5 reanalysis data. The horizontal resolution is 10km (for FESOM, the extratropical regions have a coarser grid). The output from the tropical Atlantic from these model runs is provided here, with a high temporal resolution of 3 hours, and interpolated to a 0.1°x0.1° latitude-longitude grid. Please read the readme before using the data: https://www.wdc-climate.de/ui/entry?acronym=nextGEMSWp6OceanREADME nextGEMS is funded through the European Union’s Horizon 2020 research and innovation program under the grant agreement number 101003470.

Overview

• Introduction
• Object Classes
  • Button
  • Check Box
  • Checked Radio Button
  • Checked Box
  • Dropdown Box
  • Dropdown Expand
  • Icon
  • Radio Button
  • Scroll Bar
  • Text Box

Introduction

This dataset is focused on annotating common UI elements found in graphical interfaces. Each element is crucial for understanding and interacting with digital content. The task is to accurately identify and annotate these elements to facilitate their automated detection.

• Button: A clickable rectangular area often containing text or an icon.
• Check Box: A small square used to select or deselect options.
• Checked Radio Button: A circular button indicating a selected option.
• Checked Box: A check box that has been marked.
• Dropdown Box: A horizontal rectangle with an arrow indicating a menu.
• Dropdown Expand: The expanded view of a dropdown box showing options.
• Icon: A small, symbolic graphic.
• Radio Button: A circular button used for exclusive selections.
• Scroll Bar: A thin rectangle for scrolling through content.
• Text Box: A rectangular field for inputting text.

Object Classes

Button

Description

A button is typically a rectangular area on the screen with text or an icon that can be clicked to perform an action.

Instructions

• Annotate the entire clickable region of the button, including any border or shadow.
• Do not include adjacent decorative elements such as logos unless they are part of the button.

Check Box

Description

A square element used to toggle between two states: checked or unchecked.

Instructions

• Outline the square region of the check box.
• Do not include the label text next to the check box.

Checked Radio Button

Description

A circular button that indicates a selected choice, often filled or marked.

Instructions

• Encircle the entire radio button, including the outer ring and the inner filled area.
• Exclude any text associated with the button.

Checked Box

Description

A marked square indicating selection.

Instructions

• Annotate only the square containing the check mark.
• Do not include adjacent text or icons.

Dropdown Box

Description

An interface element typically shown as a horizontal rectangle with a downward arrow, indicating a menu.

Instructions

• Outline the rectangle of the dropdown box including the arrow.
• Exclude the text or items visible inside when expanded.

Dropdown Expand

Description

The expanded view of a dropdown box, showing all selectable options.

Instructions

• Annotate the full area occupied by the menu, including visible options.
• Do not include items outside this expanded area.

Icon

Description

A small graphic symbol representing an action or object.

Instructions

• Draw a tight bounding box around the entire icon.
• Do not clip parts of the icon or include surrounding text.

Radio Button

Description

A circular UI element used for making a single choice from multiple options.

Instructions

• Circle the radio button, ensuring the boundary includes the outer circle.
• Do not include any additional elements or text.

Scroll Bar

Description

A vertical or horizontal bar used to scroll content, typically located on the edge of a screen or window.

Instructions

• Annotate the full bar, including the draggable element and background track.
• Do not include adjacent UI components.

Text Box

Description

A rectangular input field for entering text.

Instructions

• Outline the entire text box area, including any border or shadow.
• Exclude placeholder text or icons within or adjacent to the text box.

The aim of the current study is to examine what presentation preferences adults with different neurodiversities have. The specific neurodevelopmental disorders we have chosen to pursue are: ADHD, Autism, Dyslexia, Dyscalculia and Dyspraxia. The stimuli we have chosen to test are: font size, font colour, font type, line spacing, background colour, presentation of instructions, presentation of title and types of rewards. Participants were asked to complete a number of sections via an online survey. Participants were asked to rate how easy a sentence was to read for them. Each sentence had one of the following variables changed: font size, font style, spacing between characters, spacing between lines, and background colour. Each item was scored on a 5-point, Likert-type scale (1 = strongly disagree, 5 = strongly agree), so that higher scores reflected that the sentence was easy to read. Participants were also asked to rank the sentences from least favourite to favourite per variable. Participants were presented with example instructions and were asked to select the response that most accurately represented their opinion of the layout of the instructions. Each item was scored on a 5-point, Likert-type scale (1 = strongly disagree, 5 = strongly agree), so that higher scores reflected that the instructions were easy to read. Participants were presented with some example titles and had to rate how much the title in the example was distracted from the main text. Each item was scored on a 5-point, Likert-type scale (1 = strongly disagree, 5 = strongly agree), so that higher scores reflected that the title was not distracting from the main text. Participants were presented with different icons for collecting rewards and were asked to rate to what extent they would enjoy collecting rewards using those icons. Each item was scored on a 5-point, Likert-type scale (1 = strongly disagree, 5 = strongly agree), so that higher scores reflected that the icon was very enjoyable.Results indicated that all neurodiverse groups had similar preferences across all variables, with one category in each being significantly preferred across all groups. The exception to this was background colour, in which each neurodiverse group preferred a different colour.

Access API

Metadata Portal Metadata Information

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This dataset contains all the measurements used for the analysis of the respective publication. More details on the measurement setup etc. can be found in there. The data contains of three subfolders, one including the AIDA data, one the INKA and one the mul-NIPI data. Each folder contains one txt file for each experiment of the measurement campaign (see Table 2 in the publication). The name of the txt file represents the sample and the aerosolisation technique used (in case of the AIDA and INKA data). Below we give a short explanation on the data in each folder: AIDA: Each data file consists of 6 columns: temperature T ([T]=K), the uncertainty of T deltaT, the surface active site density nS ([ns]=m-2), the uncertainty of ns deltanS, the ice nucleation active site density per mass of sea salt nm ([nm]=g-1), the uncertainty of nm deltanm. The AIDA ns data were corrected for the background ice nucleation mode observed in the reference experiments with purely inorganic Sigma-Aldrich sea salt solution droplets (see Sect. 2.4 in the manuscript). There was no signal above background for the following experiments (and therefore no data file exists): SM100a AEGOR, SM10 AEGOR, SML8 AEGOR. INKA: Each data file consists of 2 columns: temperature T ([T]=°C), the surface active site density ns ([ns]=m-2). There was no signal for the following experiments (and therefore no data file exists): Sigma sea salt nebuliser, SM100a AEGOR, SML8 AEGOR. NIPI: Data files consist at least of two columns (T and FF) and additional of the following (depending on the dataset): temperature T ([T]=°C), concentration of ice nucleation particles INP ([INP]=L-1), frozen fraction FF, the ice nucleation active site density per mass of sea salt nm ([nm]=g-1), the freezing point depression corrected temperature Corrected T ([Corrected T]=°C), the upper limit of the ice nucleation active site density per mass of sea salt nm ([nm]=g-1), the lower limit of the ice nucleation active site density per mass of sea salt nm ([nm]=g-1).