Deep learning has recently been applied to
scene labelling, object tracking, pose estimation, text
detection and recognition, visual saliency detection, and
image categorization. Deep learning typically uses
models like Auto Encoder, Sparse Coding, Restricted
Boltzmann Machine, Deep Belief Networks, and
Convolutional Neural Networks. Convolutional neural
networks have exhibited good performance in picture
categorization when compared to other types of models.
A straightforward Convolutional neural network for
image categorization was built in this paper. The image
classification was finished by this straightforward
Convolutional neural network. On the foundation of the
Convolutional neural network, we also examined several
learning rate setting techniques and different
optimisation algorithms for determining the ideal
parameters that have the greatest influence on image
categorization.
Keywords :
Convolutional neural network, Deep Learning, Transfer Learning, ImageNet, Image classification; learning rate, parametric solution.