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FAQ:
Q: What does convolutional neural network (CNN) mean?
A: What Does Convolutional Neural Network (CNN) Mean? What Does Convolutional Neural Network (CNN) Mean? A convolutional neural network (CNN) is a specific type of artificial neural network that uses perceptrons, a machine learning unit algorithm, for supervised learning, to analyze data.
Q: What are CNNs?
A: CNNs are a fundamental example of deep learning, where a more sophisticated model pushes the evolution of artificial intelligence by offering systems that simulate different types of biological human brain activity.
Q: What is the output of the CNN?
A: The first (or bottom) layer of the CNN usually detects basic features such as horizontal, vertical, and diagonal edges. The output of the first layer is fed as input of the next layer, which extracts more complex features, such as corners and combinations of edges.
Q: What are the challenges of developing CNNs?
A: One of the great challenges of developing CNNs is adjusting the weights of the individual neurons to extract the right features from images. The process of adjusting these weights is called “training” the neural network. In the beginning, the CNN starts off with random weights.