Degradation-Agnostic Medicine Strip Data Enhancement via Residual Learning
摘要
In the medical field, the readability of important information on medicine packs, like the expiry date, is of prime importance for maintaining patient safety. Yet, a number of reasons like damage, blurring, and printing defects may hide this important information on medicine strips. To solve this problem, we suggest a deep learning-based solution for medicine strip denoising and enhancement, making important information such as expiry dates more legible. Our approach utilizes image denoising, specifically designed to correct blurry or partially readable expiry dates on the packaging of medicines. This solution not only helps healthcare workers and patients validate medicines but also makes a contribution to the pharmaceutical industry.