1 citations · 1 across the 4 of their papers we have counts for
4 papers
AttenCraft: Attention-guided Disentanglement of Multiple Concepts for Text-to-Image Customization
Junjie Shentu, Matthew Watson, Noura Al Moubayed
Text-to-image (T2I) customization empowers users to adapt the T2I diffusion model to new concepts absent in the pre-training dataset. On this basis, capturing multiple new concepts…
Textual Localization: Decomposing Multi-concept Images for Subject-Driven Text-to-Image Generation
Junjie Shentu, Matthew Watson, Noura Al Moubayed
Subject-driven text-to-image diffusion models empower users to tailor the model to new concepts absent in the pre-training dataset using a few sample images. However, prevalent sub…
Attack-agnostic Adversarial Detection on Medical Data Using Explainable Machine Learning
Matthew Watson, Noura Al Moubayed
Explainable machine learning has become increasingly prevalent, especially in healthcare where explainable models are vital for ethical and trusted automated decision making. Work…
Agree to Disagree: When Deep Learning Models With Identical Architectures Produce Distinct Explanations
Matthew Watson, Bashar Awwad Shiekh Hasan, Noura Al Moubayed
Deep Learning of neural networks has progressively become more prominent in healthcare with models reaching, or even surpassing, expert accuracy levels. However, these success stor…