Foundation models are AI systems trained on vast amounts of data — often trillions of individual data points — and they are capable of learning new ways of modeling information and performing a range ...
Machine Learning Practical - Coursework 2: Analysing problems with the VGG deep neural network architectures (with 8 and 38 hidden layers) on the CIFAR100 dataset by monitoring gradient flow during ...
Abstract: Batch normalization (BN) has proven to be a critical component in speeding up the training of deep spiking neural networks in deep learning. However, conventional BN implementations face ...
Abstract: The flush air data sensing (FADS) method based on artificial neural networks (ANNs) has been widely studied and applied in air data sensing for advanced aircraft. Most current methods focus ...
ABSTRACT: Pneumonia remains a significant cause of morbidity and mortality worldwide, particularly in vulnerable populations such as children and the elderly. Early detection through chest X-ray ...
AI training and inference are all about running data through models — typically to make some kind of decision. But the paths that the calculations take aren’t always straightforward, and as a model ...
This project focuses on predicting the pulse rate of a chlorine dosing pump in a drinking water treatment plant based on water characteristics. An AI model will be developed to calculate the required ...
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