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ResNets

Posts on Residual Networks

AdamW for a ResNet56v2 – II – linear LR-schedules, Adam, L2-regularization, weight decay and a reduction of training epochs

This series is about a ResNetv56v2 tested on the CIFAR10 dataset. In the last post AdamW for a ResNet56v2 – I – a detailed look at results based on the Adam optimizer we investigated a piecewise constant reduction schedule for the Learning Rate [LR] over 200 epochs. We found that we could reproduce results of R. Atienza, who had claimed… Read More »AdamW for a ResNet56v2 – II – linear LR-schedules, Adam, L2-regularization, weight decay and a reduction of training epochs

AdamW for a ResNet56v2 – I – a detailed look at results based on the Adam optimizer

This post requires Javascript to display formulas! The last days I started to work on ResNets again. The first thing I did was to use a ResNet code which Rowel Atienza has published in his very instructive book “Advanced Deep Learning with Tensorflow2 and Keras” [1]. I used the code on the CIFAR10 dataset. Atienza’s approach for this test example… Read More »AdamW for a ResNet56v2 – I – a detailed look at results based on the Adam optimizer

ResNet basics – II – ResNet V2 architecture

In the 1st post of this series ResNet basics – I – problems of standard CNNs I gave an overview over building blocks of standard Convolutional Neural Networks [CNN]. I also briefly discussed some problems that come up when we try to build really deep networks with multiple stacks of convolutional layers [e.g. Conv1D- or Conv2D-layers of the Keras framework].… Read More »ResNet basics – II – ResNet V2 architecture

ResNet basics – I – problems of standard CNNs

Convolutional Neural Networks [CNNs] do a good job regarding the analysis of image or video data. They extract correlation patterns hidden in the numeric data of our media objects, e.g. images or videos. Thereby, they get an indirect access to (visual) properties of displayed physical objects – like e.g. industry tools, vehicles, human faces, …. But there are also problems… Read More »ResNet basics – I – problems of standard CNNs