Howtosignalprocessing
- What is multi scale convolutional neural network?
- What is wavelet CNN?
- What's the difference between multi headed and multi channel CNNs?
- What is a wavelet network?
What is multi scale convolutional neural network?
The term Multi-Scale used in CNNs is mainly associated with the feature extraction part. To put it simply we can say that we take an input image and resize it to various resolutions and apply a Convolution block to it to perform feature extraction. Multi-Scale feature extraction can be done via: Dilated Convolutions.
What is wavelet CNN?
In proposed CNN architecture, wavelets are utilized to extract features in multiresolution images and also in spectral domain. Including wavelets, combines the advantage of multiresolution and spectral domain analysis into the existing CNN architectures, thereby improving its performance with a richer feature set.
What's the difference between multi headed and multi channel CNNs?
The Multi-channel CNN (MC- CNN) uses a single convolutional head with multiple chan- nels to process the time series. The Multi-head CNN (MH- CNN) uses independent single-channel convolutional heads to process each Process Variable separately.
What is a wavelet network?
Wavelet networks are a new class of networks that combine the classic sigmoid neural networks (NNs) and the wavelet analysis (WA). WNs have been used with great success in a wide range of applications. However a general accepted framework for applying WNs is missing from the literature.
