June 2018
Intermediate to advanced
378 pages
8h 43m
English
As mentioned in the introduction of this chapter, we have already been introduced to the concepts behind object recognition using CNNs. For this case, we used a trained model to perform classification; it achieved this by learning a set of feature maps using convolutional layers that are fed into fully connected (or dense) layers and, finally, their output, through an activation layer which gave us the probability for each of the classes. The class was inferred by selecting the one with the largest probability.