object detection

An Analysis of Multi-Task Architectures for the Hierarchic Multi-Label Problem of Vehicle Model and Make Classification (2026)

arXiv.org Authors Alexandru Manole, Laura Diosan Abstract Most information in our world is organized hierarchically; however, many Deep Learning approaches do not leverage this semantically rich structure. Research suggests that human learning benefits from exploiting the hierarchical structure of information, and intelligent models could similarly take advantage of this through multi-task learning. In this…

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…

UOLO: A Multitask U-Net YOLO Hybrid Model for Railway Scene Understanding (2025)

Extracting essential information including the topological structure of rail-tracks, the position of switches and their current state can increase safety by reducing human error, while also boosting the efficiency of rail transportation. Despite the impressive advancements in the field of autonomous driving, computer vision approaches in the rail domain are still a small niche.…

Analyzing the Impact of Data Augmentation on Tumor Detection and Classification in Mammograms (2025)

Breast cancer remains one of the leading causes of mortality among women worldwide, making early detection crucial for improving survival rates. Deep learning-based approaches have shown remarkable potential in automating tumor detection from mammographic images; however, their effectiveness largely depends on the choice of data augmentation strategies and model architecture. In this study, we…

GenGUI: A Dataset for Automatic Generation of Web User Interfaces Using ChatGPT (2025)

The identification of elements in user interfaces is a problem that can generate great interest in current times due to the significant interaction between users and machines. Digital technologies are increasingly used to carry out almost any daily task. Computer vision can be helpful in different applications, such as accessibility, testing, or automatic code…

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…

The Impact of Data Annotations on the Performance of Object Detection Models in Icon Detection for GUI Images (2024)

Detecting icons in Graphical User Interfaces (GUIs) is essential for effective application automation. This study examines the impact of different annotation methods on the performance of object detection models for icon detection in GUIs. We compared manual, automated, and hybrid annotations using three models: Faster R-CNN, YOLOv8, and YOLOv9. The results show that manual…