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Fine-Grained Image Analysis: Modern Approaches [electronic resource] / by Xiu-Shen Wei.

By: Wei, Xiu-Shen [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Synthesis Lectures on Computer Vision: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2023Edition: 1st ed. 2023.Description: XII, 206 p. 90 illus., 86 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031313745.Subject(s): Computer vision | Image processing -- Digital techniques | Image processing | Pattern recognition systems | Machine learning | Artificial intelligence | Computer Vision | Computer Imaging, Vision, Pattern Recognition and Graphics | Image Processing | Automated Pattern Recognition | Machine Learning | Artificial IntelligenceAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 006.37 Online resources: Click here to access online
Contents:
Introduction -- Background -- Benchmark Datasets -- Fine-Grained Image Recognition -- Fine-Grained Image Retrieval -- Resources and Future Work -- Index.
In: Springer Nature eBookSummary: This book provides a comprehensive overview of the fine-grained image analysis research and modern approaches based on deep learning, spanning the full range of topics needed for designing operational fine-grained image systems. The author begins by providing detailed background information on FGIA, focusing on recognition and retrieval. The author also provides the fundamentals of convolutional neural networks to further make it easier for readers to understand the technical content in the book. The book introduces the main technical paradigms, technological developments, and representative approaches of fine-grained image recognition and fine-grained image retrieval. The author covers multiple popular research topics and includes cross-domain knowledge. The book also highlights advanced applications and topics for future research. .
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Introduction -- Background -- Benchmark Datasets -- Fine-Grained Image Recognition -- Fine-Grained Image Retrieval -- Resources and Future Work -- Index.

This book provides a comprehensive overview of the fine-grained image analysis research and modern approaches based on deep learning, spanning the full range of topics needed for designing operational fine-grained image systems. The author begins by providing detailed background information on FGIA, focusing on recognition and retrieval. The author also provides the fundamentals of convolutional neural networks to further make it easier for readers to understand the technical content in the book. The book introduces the main technical paradigms, technological developments, and representative approaches of fine-grained image recognition and fine-grained image retrieval. The author covers multiple popular research topics and includes cross-domain knowledge. The book also highlights advanced applications and topics for future research. .

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