CT image denoising and deblurring with deep learning: current status and perspectives
This article reviews the deep learning methods for computed tomography image denoising
and deblurring separately and simultaneously. Then, we discuss promising directions in this …
and deblurring separately and simultaneously. Then, we discuss promising directions in this …
Prompt learning in computer vision: a survey
Prompt learning has attracted broad attention in computer vision since the large pre-trained
vision-language models (VLMs) exploded. Based on the close relationship between vision …
vision-language models (VLMs) exploded. Based on the close relationship between vision …
Distilling CLIP with Dual Guidance for Learning Discriminative Human Body Shape Representation
Abstract Person Re-Identification (ReID) holds critical importance in computer vision with
pivotal applications in public safety and crime prevention. Traditional ReID methods reliant …
pivotal applications in public safety and crime prevention. Traditional ReID methods reliant …
Explainable artificial intelligence (XAI): from inherent explainability to large language models
F Mumuni, A Mumuni - arxiv preprint arxiv:2501.09967, 2025 - arxiv.org
Artificial Intelligence (AI) has continued to achieve tremendous success in recent times.
However, the decision logic of these frameworks is often not transparent, making it difficult …
However, the decision logic of these frameworks is often not transparent, making it difficult …
Explainable Search and Discovery of Visual Cultural Heritage Collections with Multimodal Large Language Models
T Arnold, L Tilton - arxiv preprint arxiv:2411.04663, 2024 - arxiv.org
Many cultural institutions have made large digitized visual collections available online, often
under permissible re-use licences. Creating interfaces for exploring and searching these …
under permissible re-use licences. Creating interfaces for exploring and searching these …
[PDF][PDF] Comparative Explanations for Recommendation: Research Directions
Explanations have a long history in recommender systems. Researchers have studied the
different roles explanations can play, the value of explanations for users, and different …
different roles explanations can play, the value of explanations for users, and different …
Denoising Diffusion Path: Attribution Noise Reduction with An Auxiliary Diffusion Model
The explainability of deep neural networks (DNNs) is critical for trust and reliability in AI
systems. Path-based attribution methods, such as integrated gradients (IG), aim to explain …
systems. Path-based attribution methods, such as integrated gradients (IG), aim to explain …