Academic Articles & Research Papers

Quantum Computing for Pattern Classification

Pattern Recognition with Neural Networks in C++

From the Publisher: The addition of artificial neural network computing to traditionalpattern recognition has given rise to a new, different, and more powerful methodology that is presented in this interesting book. This is a practical gui...

Fundamentals of neural networks: architectures, algorithms, and applications

1. Introduction. 2. Simple Neural Nets for Pattern Classification. 3. Pattern Association. 4. Neural Networks Based on Competition. 5. Adaptive Resonance Theory. 6. Backpropagation Neural Net. 7. A Sampler of Other Neural Nets. Glossary. Re...

Applications of Neural Networks in Electromagnetics

From the Book: Since the early 1990s, a plethora of electromagnetic problems have been tackled using neural networks, some more successfully than others. Because neural networks and electromagnetics are two different scientific fields, not...

Computer vision for microscopy diagnosis of malaria

This paper reviews computer vision and image analysis studies aiming at automated diagnosis or screening of malaria infection in microscope images of thin blood film smears. Existing works interpret the diagnosis problem differently or prop...

Template Matching Techniques in Computer Vision

The detection and recognition of objects in images is a key research topic in the computer vision community. Within this area, face recognition and interpretation has attracted increasing attention owing to the possibility of unveiling huma...

Computer Vision and Image Processing

The book familiarizes readers with fundamental concepts and issues related to computer vision and major approaches that address them. The focus of the book is on image acquisition and image formation models, radiometric models of image form...

Neural Networks for Pattern Recognition

In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Neural Networks for Pattern Recognition takes the pioneering work in artificial neural network...

Building neural networks

Foundations. Motivation. Neural-Network Fundamentals. Single Neuron Computations. Network Computations. Network Simulation. Foundations Summary. Suggested Readings. Bibliography. Paradigms. The Backpropagation Network. The Counterpropagatio...

Invariant representation of physical stability in the human brain

Successful engagement with the world requires the ability to predict what will happen next. Here, we investigate how the brain makes a fundamental prediction about the physical world: whether the situation in front of us is stable, and henc...

Artificial neural networks

Artificial neural networks are explained, and the different types are described. Three different tasks for which they are suitable are discussed. They are pattern classification and associative memory, self-organization and feature extracti...

Neural Network Learning

First published in 1999, this book describes theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. R...

On neural networks.

JIŘÍ BENEŠTypical neural network models representing a broad survey of actual trends are considered in an unifying way as Complexes subject to specific control systems, called Formators which may have a two-level arrangement and incorporate...

A tutorial survey of architectures, algorithms, and applications for deep learning

In this invited paper, my overview material on the same topic as presented in the plenary overview session of APSIPA-2011 and the tutorial material presented in the same conference [1] are expanded and updated to include more recent develop...