An introduction to the various types of models in deep convolutional neural networks

A deep convolutional neural network (DCNN) is a deep learning technique that helps computers identify features from complex image or audio data. DCNNs can be used to solve many computer vision and speech recognition tasks, including image classification, object detection, speech recognition, and natural language processing. Common models in DCNN include: convolutional neural network (CNN), long short-term memory (LSTM), recurrent neural network (RNN), adaptive pooling (AP) and attention mechanism (AM).