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Full-Text Articles in Physical Sciences and Mathematics
Contrast Enhancement Of Ultrasound Images Using Shunting Inhibitory Cellular Neural Networks, Murali M. Gogineni
Contrast Enhancement Of Ultrasound Images Using Shunting Inhibitory Cellular Neural Networks, Murali M. Gogineni
Theses: Doctorates and Masters
Evolving from neuro-biological insights, neural network technology gives a computer system an amazing capacity to actually generate decisions dynamically. However, as the amount of data to be processed increases, there is a demand for developing new types of networks such as Cellular Neural Networks (CNN), to ease the computational burden without compromising the outcomes. The objective of this thesis is to research the capability of Shunting Inhibitory Cellular Neural Networks (SICNN) to solve the clarity problems in ultrasound imaging. In this thesis, we begin by reviewing a number of traditional enhancement techniques and measures. Since the entire work of this …
A Generalised Feedforward Neural Network Architecture And Its Applications To Classification And Regression, Ganesh Arulampalam
A Generalised Feedforward Neural Network Architecture And Its Applications To Classification And Regression, Ganesh Arulampalam
Theses: Doctorates and Masters
Shunting inhibition is a powerful computational mechanism that plays an important role in sensory neural information processing systems. It has been extensively used to model some important visual and cognitive functions. It equips neurons with a gain control mechanism that allows them to operate as adaptive non-linear filters. Shunting Inhibitory Artificial Neural Networks (SIANNs) are biologically inspired networks where the basic synaptic computations are based on shunting inhibition. SIANNs were designed to solve difficult machine learning problems by exploiting the inherent non-linearity mediated by shunting inhibition. The aim was to develop powerful, trainable networks, with non-linear decision surfaces, for classification …