04086nam 22007935 450 991014402580332120200701161246.03-540-45169-210.1007/b11963(CKB)1000000000212118(SSID)ssj0000323753(PQKBManifestationID)11241059(PQKBTitleCode)TC0000323753(PQKBWorkID)10303298(PQKB)10200284(DE-He213)978-3-540-45169-3(MiAaPQ)EBC3088518(PPN)155186086(EXLCZ)99100000000021211820121227d2003 u| 0engurnn|008mamaatxtccrHierarchical Neural Networks for Image Interpretation /by Sven Behnke1st ed. 2003.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2003.1 online resource (XIII, 227 p.) Lecture Notes in Computer Science,0302-9743 ;2766Bibliographic Level Mode of Issuance: Monograph3-540-40722-7 Includes bibliographical references and index.I. Theory -- Neurobiological Background -- Related Work -- Neural Abstraction Pyramid Architecture -- Unsupervised Learning -- Supervised Learning -- II. Applications -- Recognition of Meter Values -- Binarization of Matrix Codes -- Learning Iterative Image Reconstruction -- Face Localization -- Summary and Conclusions.Human performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably under a wide range of conditions, computer vision systems work well only under controlled conditions in limited domains. This book sets out to reproduce the robustness and speed of human perception by proposing a hierarchical neural network architecture for iterative image interpretation. The proposed architecture can be trained using unsupervised and supervised learning techniques. Applications of the proposed architecture are illustrated using small networks. Furthermore, several larger networks were trained to perform various nontrivial computer vision tasks.Lecture Notes in Computer Science,0302-9743 ;2766ComputersNeurosciencesAlgorithmsArtificial intelligenceOptical data processingPattern perceptionComputation by Abstract Deviceshttps://scigraph.springernature.com/ontologies/product-market-codes/I16013Neuroscienceshttps://scigraph.springernature.com/ontologies/product-market-codes/B18006Algorithm Analysis and Problem Complexityhttps://scigraph.springernature.com/ontologies/product-market-codes/I16021Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Image Processing and Computer Visionhttps://scigraph.springernature.com/ontologies/product-market-codes/I22021Pattern Recognitionhttps://scigraph.springernature.com/ontologies/product-market-codes/I2203XComputers.Neurosciences.Algorithms.Artificial intelligence.Optical data processing.Pattern perception.Computation by Abstract Devices.Neurosciences.Algorithm Analysis and Problem Complexity.Artificial Intelligence.Image Processing and Computer Vision.Pattern Recognition.006.37Behnke Svenauthttp://id.loc.gov/vocabulary/relators/aut564937MiAaPQMiAaPQMiAaPQBOOK9910144025803321Hierarchical neural networks for image interpretation954166UNINA