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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 with standard CNNs. They have a tendency to eliminate some small scale patterns. Visually this leads to smoothing or smear-out effects. Due to an interference… Read More »ResNet basics – I – problems of standard CNNs