activity
20192026
most citedModel-agnostic explainable artificial intelligence for object detection in image data

21 citations · 38 across the 6 of their papers we have counts for

collaborators

7 papers

cs.SE2026

An empirical study of LoRA-based fine-tuning of large language models for automated test case generation

Milad Moradi, Ke Yan, David Colwell +1

Automated test case generation from natural language requirements remains a challenging problem in software engineering due to the ambiguity of requirements and the need to produce…

cs.CV2026

Multi-modal user interface control detection using cross-attention

Milad Moradi, Ke Yan, David Colwell +2

Detecting user interface (UI) controls from software screenshots is a critical task for automated testing, accessibility, and software analytics, yet it remains challenging due to…

cs.SE2024

Artificial intelligence for context-aware visual change detection in software test automation

Milad Moradi, Ke Yan, David Colwell +1

Automated software testing is integral to the software development process, streamlining workflows and ensuring product reliability. Visual testing, particularly for user interface…

cs.AI2024★ 16 cited

A critical review of methods and challenges in large language models

Milad Moradi, Ke Yan, David Colwell +2

This critical review provides an in-depth analysis of Large Language Models (LLMs), encompassing their foundational principles, diverse applications, and advanced training methodol…

cs.CV2023★ 21 cited

Model-agnostic explainable artificial intelligence for object detection in image data

Milad Moradi, Ke Yan, David Colwell +2

In recent years, deep neural networks have been widely used for building high-performance Artificial Intelligence (AI) systems for computer vision applications. Object detection is…

eess.IV2019★ 1 cited

U-Net with spatial pyramid pooling for drusen segmentation in optical coherence tomography

Rhona Asgari, Sebastian Waldstein, Ferdinand Schlanitz +3

The presence of drusen is the main hallmark of early/intermediate age-related macular degeneration (AMD). Therefore, automated drusen segmentation is an important step in image-gui…

eess.IV2019

Multiclass segmentation as multitask learning for drusen segmentation in retinal optical coherence tomography

Rhona Asgari, José Ignacio Orlando, Sebastian Waldstein +4

Automated drusen segmentation in retinal optical coherence tomography (OCT) scans is relevant for understanding age-related macular degeneration (AMD) risk and progression. This ta…