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Found 3 papers, 1 papers with code
Artificial intelligence for context-aware visual change detection in software test automation
Leveraging a machine learning model, our method accurately identifies UI controls from software screenshots and constructs a graph representing contextual and spatial relationships between the controls.
Exploring the landscape of large language models: Foundations, techniques, and challenges
In this review paper, we delve into the realm of Large Language Models (LLMs), covering their foundational principles, diverse applications, and nuanced training processes.
Model-agnostic explainable artificial intelligence for object detection in image data
In this paper, we design and implement a black-box explanation method named Black-box Object Detection Explanation by Masking (BODEM) through adopting a hierarchical random masking approach for AI-based object detection systems.
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