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|a 9783319583471
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|a 10.1007/978-3-319-58347-1
|2 doi
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|a Sistema de Bibliotecas del Tecnológico de Costa Rica
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|a Domain Adaptation in Computer Vision Applications /
|c edited by Gabriela Csurka.
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|a 1st ed. 2017.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2017.
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|a X, 344 p. 107 illus., 101 illus. in color. :
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a Advances in Computer Vision and Pattern Recognition,
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|a A Comprehensive Survey on Domain Adaptation for Visual Applications -- A Deeper Look at Dataset Bias.- Part I: Shallow Domain Adaptation Methods -- Geodesic Flow Kernel and Landmarks: Kernel Methods for Unsupervised Domain Adaptation -- Unsupervised Domain Adaptation based on Subspace Alignment -- Learning Domain Invariant Embeddings by Matching Distributions -- Adaptive Transductive Transfer Machines: A Pipeline for Unsupervised Domain Adaptation -- What To Do When the Access to the Source Data is Constrained?.- Part II: Deep Domain Adaptation Methods -- Correlation Alignment for Unsupervised Domain Adaptation -- Simultaneous Deep Transfer Across Domains and Tasks -- Domain-Adversarial Training of Neural Networks.- Part III: Beyond Image Classification -- Unsupervised Fisher Vector Adaptation for Re-Identification -- Semantic Segmentation of Urban Scenes via Domain Adaptation of SYNTHIA -- From Virtual to Real World Visual Perception using Domain Adaptation – The DPM as Example -- Generalizing Semantic Part Detectors Across Domains.- Part IV: Beyond Domain Adaptation: Unifying Perspectives -- A Multi-Source Domain Generalization Approach to Visual Attribute Detection -- Unifying Multi-Domain Multi-Task Learning: Tensor and Neural Network Perspectives.
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|a Optical data processing.
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|a Artificial intelligence.
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|a Application software.
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|a Image Processing and Computer Vision.
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|a Artificial Intelligence.
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|a Computer Appl. in Administrative Data Processing.
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|a Csurka, Gabriela.
|e editor.
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|a SpringerLink (Online service)
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|t Springer eBooks
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