Convolutional Neural Networks(CNN) becomes popular in Image recognition, such as Image Search, Autonomous self-driving cars, and other visual applications. In this blog, we will see Convolutional Neural Networks(CNN) Layers, Convolutional Neural Networks(CNN) Filters, and Convolutional Neural Networks(CNN) Architectures.
As we talked about ImageNet, MNIST, and Fashion-MNIST datasets and also types of Neural Networks, we will go deeper into many Convolutional Neural Networks(CNN) related topics in future blogs.
Convolutional Neural Networks(CNN) has three layers:
- Convolutional layers
- Pooling layers
- Dense layers
Different types of Convolutional Neural Networks(CNN) filters (kernels):
- Identity
- Edge Detection
- Sharpen
- Box blur
- Gaussian blur
Popular Convolutional Neural Networks(CNN) Architectures:
- LeNet-5
- AlexNet
- GoogLeNet
- VGGNet
- ResNET
- Xception
- Xception
- SENet
We will get deeper in future blogs on each architecture and its use in real-time scenarios.
Leave A Comment