Concatenation skips stack outputs like Lego bricks ... Decreasing back-propagation distance Early CNN layers have a much smaller receptive field and tend to learn simple features (edges or ...

We stack 3 CNN layers based on the config, then a 4th one with linear activation and n 1x1 filters, where n is the number of actions in the (discrete) action space.

"CNN should be deeply embarrassed that despite layers and layers of editorial staff, they could not perform basic journalistic functions nor overcome clear dysfunction among overpaid, arrogant TV ...

This was my first attempt at visualizing the features learnt by the layers of a neural net. In this notebook, I trained a simple neural network on the MNIST dataset. My architecture consisting of 2 ...

In this project, different CNN Architectures like VGG-16(with and without SPP Layer), VGG-19(with and without SPP Layer), and ResNet-50(with and without SPP Layer) were used for the task of Dog-Cat ...

The model structure is like below. We use Deep CNN with Residual Net, Skip Connection and Network in Network. A combination of Deep CNNs and Skip connection layers is used as a feature extractor for ...