Would you be able to explain the "slice and dice" method for the multidimensional model?

Suppose you are designing a deep learning architecture to solve an object detection problem, where there areN numbers of objects and each object has M number of images. If the resolution of each image is 227 x 227 x 3, then answer the following questions: (a) Write down the name of the layers of your deep learning architecture including parameters dimension. (b) How many convolution layers will you use in your deep learning model and why? (c) Is it a good idea to use multiple fully connected layers? Motivate your answer

Implement a Multi-layer perceptron model and test the model using any data set of your choice. The output should include Accuracy, Error rate, Precision, and recall rate along with the confusion matrix.