Advanced Convolutional Neural Network Architecture : A Detailed Review
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2019 by IJETT Journal|
|Year of Publication : 2019|
|Authors : Suresh Arunachalam T, Shahana R, Kavitha T
|DOI : 10.14445/22315381/IJETT-V67I5P231|
MLA Style: Suresh Arunachalam T, Shahana R, Kavitha T"Advanced Convolutional Neural Network Architecture : A Detailed Review" International Journal of Engineering Trends and Technology 67.5 (2019):183-187.
APA Style:Suresh Arunachalam T, Shahana R, Kavitha T (2019).Advanced Convolutional Neural Network Architecture : A Detailed Review International Journal of Engineering Trends and Technology,67(5),183-187
Deep Learning is a part of Machine Learning algorithm. It looks and works like a brain, it is also known as Artificial Neural Networks and it is trained from a large amount of data. Now-a-days deep learning technology plays a vital role in many fields such as an object detection, classification, image segmentation and recognition. In this paper, we discussed benefits, issues and applications of advanced architecture available in deep learning networks. Generally, deep learning architecture consists of three layers namely, input layer, hidden layers (Convolutional layers, Pooling layers and activation layers), and output layer. The learning can be achieved by any of the supervised, unsupervised, reinforcement algorithms. The common issues in the architectures fall under the requirement for larger dataset to train the neural network and it consumes more time to train the network.
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Deep Learning, Advanced Architecture, CNN.