ResNet

ResNet, short for Residual Network, is a type of deep learning model used in computer vision tasks, like image recognition. It helps computers learn to identify patterns in images by using layers of artificial neurons. What makes ResNet special is its use of "skip connections," allowing the model to jump over certain layers. This helps in avoiding problems like degradation, where adding more layers can actually hurt performance. As a result, ResNet can be very deep, learning more complex features while maintaining accuracy, and has been highly effective in various image classification challenges.