CNN Architectures in Deep Learning 🧠

Convolutional Neural Networks (CNNs) are pivotal in computer vision tasks. Here's a breakdown of key architectures and concepts:

📘 Classic CNN Structures

• LeNet (1998): Pioneered CNNs for handwritten digit recognition
• AlexNet (2012): Revolutionized ImageNet competition with deeper layers
• VGGNet (2014): Known for simplicity and uniformity in convolutional layers

🔬 Modern Innovations

• ResNet (2015): Introduced residual blocks for deeper networks
• DenseNet (2017): Features dense connections between layers
• EfficientNet (2019): Optimized scaling of depth/width/resolution

📚 Recommended Learning Path

1. Deep Learning Fundamentals
2. CNN Implementation Guide
3. Advanced Architectures

🧪 Practical Applications

• Object detection (YOLO, SSD)
• Image segmentation (U-Net)
• Generative models (GANs, VAEs)

For visual comparisons of architecture designs:

Explore our Deep Learning Course Catalog for hands-on projects!