ABSTRACT: Convolutional neural networks (CNNs) are widely used in image classification tasks, but their increasing model size and computation make them challenging to implement on embedded systems ...

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 ...

Cytometry by Time-Of-Flight (CyTOF) uses antibodies conjugated to isotopically pure metals to identify and quantify a large number of cellular features with single-cell resolution. A barcoding ...

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 ...

Abstract: Batch normalization (BN) is a fundamental unit in modern deep neural networks. However, BN and its variants focus on normalization statistics but neglect the recovery step that uses linear ...

Originally, this work was a term project for for Florida Atlantic University's CAP-6619 Deep Learning class term project, Fall 2018. The report that originated the paper is available here. Since its ...