title: An introduction to bio-inspired artificial neural network architectures.
abstract: In this introduction to artificial neural networks we attempt to give an overview of the most important types of neural networks employed in engineering and explain shortly how they operate and also how they relate to biological neural networks. The focus will mainly be on bio-inspired artificial neural network architectures and specifically to neo-perceptions. The latter belong to the family of convolutional neural networks. Their topology is somewhat similar to the one of the human visual cortex and they are based on receptive fields that allow, in combination with sub-sampling layers, for an improved robustness with regard to local spatial distortions. We demonstrate the application of artificial neural networks to face analysis--a domain we human beings are particularly good at, yet which poses great difficulties for digital computers running deterministic software programs.
authors.affiliation: Beat.Fasel@idiap.ch
authors.forename: B
authors.initials: B
authors.lastname: Fasel
mesh_terms: D000818:Animals; D006801:Humans; D009415:Nerve Net / Q000033:anatomy & histology* / Q000502:physiology*; D016571:Neural Networks, Computer; D010775:Photic Stimulation / Q000379:methods; D021641:Recognition, Psychology / Q000502:physiology