This study implements a Conditional Generative Adversarial Network (CGAN) to enhance the contrast of fetal abdominal ultrasound images. The novelty lies in increasing the Reconstruction Loss weight (λL1) to 1000 to ensure structural stability in medical data. Using U-Net and PatchGAN architectures, the model was trained against CLAHE targets. The results demonstrate significant enhancement wit…
Nutrition facts tables on food packaging are a crucial source of information for consumers, but manual data extraction is often inefficient and prone to errors due to varied table structures and small text sizes. This research proposes an automated system for text detection and recognition in nutrition tables by integrating two advanced deep learning models: PaddleOCR and TrOCR. PaddleOCR is em…