Deep Learning CNN Convolutional Neural Networks with Python - Classical CNNs Activity

The video tutorial covers various neural network architectures, including LeNet, AlexNet, VGG, Inception, GoogleNet, and ResNet. It provides an activity for students to compare Inception and ResNet by reading relevant papers or blogs. The goal is to understand the strengths and weaknesses of these networks and their applications. This theoretical exercise aims to enhance understanding of state-of-the-art convolutional neural networks.

Which of the following architectures was mentioned first in the video?

• LeNet

• InceptionNet

• AlexNet

• ResNet

What is the primary task for the module activity?

• Reading and comparing network architectures

• Testing network performance

• Designing a new architecture

• Implementing a neural network

Which two architectures are specifically compared in the module activity?

• VGGNet and GoogleNet

• AlexNet and ResNet

• LeNet and AlexNet

• InceptionNet and ResNet

What is the focus of understanding the differences between InceptionNet and ResNet?

• To improve coding skills

• To enhance understanding of state-of-the-art CNNs

• To develop new algorithms

• To increase computational efficiency

Why is it important to understand the strengths and weaknesses of InceptionNet and ResNet?

• To choose the best network for specific tasks

• To simplify network design

• To reduce training time

• To minimize data requirements