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3D Convolutional Neural Networks for Solving Complex Digital Agriculture and Medical Imaging Problems
(University of Winnipe, 2022-06)
3D signals have become widely popular in view of the advantage they provide via 3D representations of data by employing a third spatial or temporal dimension to extend 2D signals. Predominantly, 3D signals contain details ...
N-Dimensional Polynomial Neural Networks and their Applications
(University of Winnipeg, 2022-04-06)
In addition to being extremely non-linear, modern machine learning problems require millions if not billions of parameters to solve or at least to get a good approximation of the solution, and neural networks are known ...