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Java Deep Learning Projects by Md. Rezaul Karim

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Current trends

As discussed in Chapter 1Getting Started with Deep Learning, researchers have recently proposed so many emergent DL architectures. These include not only improving CNN/RNN and their variants but also some other special types of architecture: Deep SpatioTemporal Neural Networks (DST-NNs), Multi-Dimensional Recurrent Neural Networks (MD-RNNs), Convolutional AutoEncoders (CAEs), deep embedding clustering, and so on.

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 as proposed by Hinton et al. Then we have residual neural networks for image recognition and Generative Adversarial Networks (GANs) for simple image generation. ...

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