Evaluating Deep Learning Models for Cross-Platform UI Component Detection: A Study Across Web, Desktop, and Mobile Interfaces (2025)

User interfaces look different across web, desktop, and mobile platforms — not just in layout, but in how buttons, icons, and text appear. This makes it hard for deep learning models trained on one platform to accurately detect UI components on another. In this paper, we evaluate the cross-domain generalization of three modern object…

The Impact of Augmentation Techniques on Icon Detection Using Machine Learning Techniques (2024)

This article examines the use of image augmentation techniques to improve icon detection in mobile interfaces, a critical task due to the small size of graphical user interface (GUI) elements and the insufficiency of comprehensive datasets. It evaluates whether diversifying the dataset or using specific augmentation methods alone can enhance detection performance. The study…

Comparing Automatic Approaches for Mvc Architecture Detection in Ios Codebases (2022)

Model View Controller (MVC) is one of the most widespread and used software architecture in client-side software. We are interested in automatically inferring and analyzing MVC architectures from mobile application codebases that could help to identify the architectural problems earlier in the development process, offering insightful knowledge for both software developers, architects, and the…

Validating HyDe: Intelligent Method for Inferring Software Architectures from Mobile Codebase (2021)

Interacting with businesses, searching for information, or accessing news and entertainment sources all have a common feature, they are predominately accessed nowadays from mobile applications. The software architecture used in building those kinds of products represents a major factor in their lifecycle, costs, and roadmap, as it affects their maintainability and extensibility. In this…