A Novel ANN Structure for Image Recognition

Neural networks in biological systems consist of various Recently, Deep Learning (DL) systems have been very kinds of neurons, each performing a specific function. Role of successful in solving complex problems like image specific neurons depends on various factors like their recognition, robotic motion control and natural language structure, position in the network, connectivity, dendrite processing. Some of the popular DL systems include the density, length of axon, neurotransmitters and inhibitors used, Convolutional Neural Networks (CNNs) [1] [2] for image chemical receptors and gateways, type of input and output, recognition, Long Short-Term Memory (LSTM) [3] for timing response and a plethora of other factors. It is therefore robotic control and time series prediction, Generative important to explore various neural architectures to move Adversarial Networks (GANs) [4] for image synthesis etc. towards realization of anything closer to Artificial General Deep Learning systems are computationally intensive.