Mobile Applications images & Logos

Published: 20 August 2024| Version 1 | DOI: 10.17632/nvxjm84n6f.1
Contributor:
RAMNATH M

Description

A mobile applications images and logos dataset typically consists of a collection of images representing the logos or user interfaces of various mobile apps. These datasets are commonly used for tasks such as logo recognition, mobile app classification, brand detection, and user interface analysis in the fields of computer vision and machine learning. Dataset Components: Images of Logos: This includes a wide variety of app logos, ranging from popular apps to lesser-known ones. Logos can be in different formats (e.g., PNG, JPG) and may vary in size and resolution. The dataset might contain both full-color logos and monochrome variations. App Icons: Apart from the logo, the dataset may contain app icons as they appear on mobile devices' home screens. These icons are typically square or rounded in shape, with resolutions like 512x512 or 1024x1024 pixels. User Interface (UI) Screenshots: Some datasets also include screenshots of the mobile app’s interface, capturing various screens like the home screen, settings, or functional pages. This component is useful for UI/UX analysis, app design comparison, or screen element recognition. Class Labels: Each image in the dataset is usually associated with metadata or labels. These labels may include: App Name: The name of the mobile application. Category: The app’s category (e.g., Social Media, Finance, Gaming, etc.). Brand Name: The brand associated with the app (e.g., Facebook, Twitter). Platform: The operating system for which the app was developed (iOS, Android). Resolution: The size or pixel dimensions of the image. Image Annotations: Some datasets may provide additional annotations, such as bounding boxes around logos or key design elements. These annotations are essential for object detection or logo localization tasks. Typical Uses: Logo Recognition: Mobile app logos are used in machine learning algorithms to recognize brands or products automatically from images or videos. App Classification: The dataset can help classify images of app interfaces into predefined categories, such as social media, gaming, or finance. Brand Analysis: The dataset allows researchers to study how logos evolve over time, or how brand identity is reflected in app icons. User Interface (UI) Research: UI screenshots can be analyzed to understand app design patterns, common layouts, or usability across different categories of mobile applications. Collection Process: Web Scraping: App logos, icons, and UI screenshots are often collected from app stores (Google Play, Apple App Store) through web scraping techniques. Manual Curation: In some cases, datasets are manually curated, where researchers download app images and organize them according to specific categories or criteria.

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Institutions

Anna University Chennai

Categories

Computer Vision, Mobile Computing

Licence