What does "CBAM" mean?
Table of Contents
CBAM stands for Convolutional Block Attention Module. It is a tool used in deep learning models to improve their performance, especially in tasks like image classification.
How CBAM Works
CBAM works by focusing on the important parts of an image. It looks at two aspects: where to pay attention in the image and what features are most relevant. This process helps the model to make better decisions based on the images it analyzes.
Benefits of Using CBAM
By using CBAM, models can become more accurate. This is because CBAM helps the model learn which parts of the image matter the most, allowing it to better distinguish between different categories, such as healthy and unhealthy conditions in medical images.
Applications of CBAM
CBAM is often used in medical fields, like ophthalmology and gynecology, where careful image analysis is crucial. It helps doctors better assess risks and make more informed decisions based on the images they work with.