Different Convolution Neural Network Based Models for Garbage Detection: A Review

Over the last couple of years, deep learning technology made tremendous progress to computer vision. The convolution neural networks have attained state-of-art performance on tasks such as the ImageNet Large Scale Visual Recognition Challenge (ILSVRC). The deep convolution neural network models are trained by deep learning algorithms. In this paper firstly describe the development of deep learning and convolution neural network. The author introduces the basic model structure of the different CNN models, feature extraction, and max-pooling operation in the convolution neural network. This paper is basically focused on the deep learning techniques related to the convolution neural network like Le-Net 5, AlexNet, GoogleNet, etc. Then, the research development trend of deep convolution neural network models related to deep learning in object detection are reviewed.