Being able to learn PDEs, PINNs have several advantages over conventional methods. PINNs, in particular, are mesh-free methods that enable on-demand solution computation after a training stage, and they allow solutions to be made differentiable using analytical gradients. Finally, they provide an ea...
where fi denotes the normalization value to 50-dimension from the bow-to-stern axis. 2.1.3. CNN-Based Models CNN-based models can learn multi-level representations of ships from much training data. These representations are usually abstract, which are often hard to understand. Despite all this...
The first block has 64 filters, while the second and third block have 128 filters, each with a kernel size of eight, five and three. The first two convolutions of each block are followed by batch normalization and a ReLu activation function, while the third convolution is followed by batch...