Retina Models

Retina models are neural network architectures designed to analyze images efficiently. Inspired by the biological retina, these models process visual information through multiple specialized pathways, capturing details at different scales. This approach allows them to recognize objects, segment images, and perform other vision tasks more accurately and quickly. Retina models are often used in applications like medical imaging, autonomous vehicles, and facial recognition, leveraging their ability to interpret complex visual data with high precision. They balance detailed feature extraction with computational efficiency, making them powerful tools for modern image analysis.