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Best ResNet variant
What do you like best about the product?
Performs better than most of the other ResNet variants
The model will easily fit in 8GB GPU/Google Colab/Kaggle Notebooks
The model will easily fit in 8GB GPU/Google Colab/Kaggle Notebooks
What do you dislike about the product?
Vanishing gradient is a major problem in residual networks. This gives NaN as an output
It overfits when the resolution of the image is small. Pooling needs to be adjusted
It overfits when the resolution of the image is small. Pooling needs to be adjusted
What problems is the product solving and how is that benefiting you?
It introduces a new dimension to the ResNet called Cardinality
It's considered the most important dimension in neural networks where they split the input, transform it and aggregate the outputs
It's considered the most important dimension in neural networks where they split the input, transform it and aggregate the outputs
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