It is a well-known fact that all the Artificial Intelligence (AI)researches happening across multiple verticals such as Neuro Imaging, Computer Vision, Deep learning etc point to one master goal of modelling the human brain function by understanding how each part of the brain works. The Convolution neural network (CNN) is one of best deep architecture suitable to handle variety of inputs. In this paper we explore the different types of input data the CNN deep architecture can process and some of the CNN configuration changes that has proved good Accuracy. We have highlighted those specialized CNN architectures along with different types of data inputs they handle including the Functional Magnetic Resonance (fMRI) Neuro Image brain data input.
CITATION STYLE
Catherine Tamilarasi, F., & Shanmugam, J. (2019). Artificial intelligence – State of art convolution neural network architectures in a nutshell. International Journal of Innovative Technology and Exploring Engineering, 8(11 Special Issue), 1278–1280. https://doi.org/10.35940/ijitee.K1257.09811S19
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