Convolutional encoding is a process of adding redundancy to a signal stream. Lattice's Convolutional Encoder core is a parameterizable core for convolutional encoding of a continuous input data stream ...

In image segmentation by deep learning, encoder-decoder Convolutional Neural Network (CNN) architectures are fundamental for creating and learning representations. However, with many filters in these ...

Specifically, depth-wise separable convolution supplants traditional linear projection within the Transformer, facilitating efficient learning of local contextual dynamics. Further, the adoption of an ...

Part 2 takes a somewhat deeper dive into the technology, briefly describing some of the most important ones including, the protocol stack, randomizer, Reed-Solomon encoder, convolution encoder, ...

An autoencoder is an unsupervised neural network that encodes input images into lower-dimensional representations and decodes them back, aiming for identical outputs. We use the MNIST dataset, ...