6 papers
Investigating the Impact of Various Loss Functions and Learnable Wiener Filter for Laparoscopic Image Desmoking
Chengyu Yang, Chengjun Liu
To rigorously assess the effectiveness and necessity of individual components within the recently proposed ULW framework for laparoscopic image desmoking, this paper presents a com…
Privacy-Preserving Automated Rosacea Detection Based on Medically Inspired Region of Interest Selection
Chengyu Yang, Rishik Reddy Yesgari, Chengjun Liu
Rosacea is a common but underdiagnosed inflammatory skin condition that primarily affects the central face and presents with subtle redness, pustules, and visible blood vessels. Au…
Patch-based Automatic Rosacea Detection Using the ResNet Deep Learning Framework
Chengyu Yang, Rishik Reddy Yesgari, Chengjun Liu
Rosacea, which is a chronic inflammatory skin condition that manifests with facial redness, papules, and visible blood vessels, often requirs precise and early detection for signif…
Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter
Chengyu Yang, Chengjun Liu
Laparoscopic surgeries often suffer from reduced visual clarity due to the presence of surgical smoke originated by surgical instruments, which poses significant challenges for bot…
Interpretable Automatic Rosacea Detection with Whitened Cosine Similarity
Chengyu Yang, Chengjun Liu
According to the National Rosacea Society, approximately sixteen million Americans suffer from rosacea, a common skin condition that causes flushing or long-term redness on a perso…
Increasing Rosacea Awareness Among Population Using Deep Learning and Statistical Approaches
Chengyu Yang, Chengjun Liu
Approximately 16 million Americans suffer from rosacea according to the National Rosacea Society. To increase rosacea awareness, automatic rosacea detection methods using deep lear…