#ResNet

Articles about ResNet — exploring patterns, best practices, and real-world implementations in production systems.

1 post tagged with resnet. ← All posts

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Pratik Dhanave · ·6 min read

CNN Architectures — How Networks Got Deeper and Better

Once convolution proved it could crack vision, the race was on to build better CNNs — and the story of how they improved is a compact lesson in deep learning itself. From AlexNet to VGG to ResNet, each landmark architecture solved a specific problem that was blocking progress, and the solutions (depth, small filters, skip connections) became foundational ideas used far beyond vision. This post traces that evolution and the principles it taught.

From AlexNet (which launched deep learning) to VGG (small filters, deep) to ResNet (skip connections that made very deep networks trainable), each landmark solved a specific blocker. ResNet's residual connection generalized everywhere — including every transformer block — so the arc is a compact lesson in deep learning itself.

#Computer Vision#CNN#ResNet#Deep Learning#Machine Learning

All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.