Beschreibung
Deep learning is a hot research topic these days. Neural networks are the workhorses of deep learning. In this research the basics of neural networks were studied. ANNs may be defined as structures comprised of densely interconnected adaptive simple processing elements (called artificial neurons or nodes) that are capable of performing massively parallel computations for data processing and knowledge representation. Definition of artificial neural network was mentioned, design of neural network was discussed, learning of neural network was studied, the most popular types of neural net- worksuch as Hopfield networks, Adaptive resonance theory (ART) networks, Kohonen networks, Backpropagation networks, Recurrent networks, Counter propagation networks and Radial basis function (RBF) networks were discussed.Also General issues in ANN development were studied.
Autorenporträt
Pofessor in surveying and photogrammetry. MSc. and B.Sc in surveying Engineering. Head of the Aviation and aerial photography division -NARSS-Egypt. More than 50 National/International Conference Publications. Almost 20 Research projects participations. MAIN RESEARCH AREA: Geomatics-Remote sensing-surveying-Digital photogrammetry.
