Emergent architectures

Many other emergent DL architectures have been suggested, such as Deep SpatioTemporal Neural Networks (DST-NNs), Multi-Dimensional Recurrent Neural Networks (MD-RNNs), and Convolutional AutoEncoders (CAEs).

Nevertheless, there are a few more emerging networks, such as CapsNets (which is an improved version of a CNN, designed to remove the drawbacks of regular CNNs), RNN for image recognition, and Generative Adversarial Networks (GANs) for simple image generation. Apart from these, factorization machines for personalization and deep reinforcement learning are also being used widely.