5.3 Advanced CNN Techniques (ResNet, Inception, DenseNet)
While basic CNNs have proven effective for image classification tasks, advanced architectures such as ResNet, Inception, and DenseNet have significantly expanded the capabilities of deep learning in computer vision. These sophisticated models address critical challenges in neural network design and training, including:
Network Depth: ResNet's innovative skip connections enable the construction of incredibly deep networks, with some implementations surpassing 1000 layers. This architectural breakthrough effectively mitigates the vanishing gradient problem, allowing for more efficient training of very deep neural networks.
Multi-scale Feature Learning: Inception's unique design incorporates ...