1. Suppose you are required to design a neural network classification system to automatically recognize fish within predefined categories as illustrated in Figure 2. There are 23 classes of fishes, each with 700 images, and each image can be represented by a 100-dimensional feature vector.

   (a) Describe the neural network model for the classification task. (b) If the performance of your model on the training set is good, but the test set performance is significantly worse, what is the most probable problem? And discuss a simple way that may improve your results. (c) If you needed even more accurate results, what kind of approaches would you try?

Figure 2: Fish images