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230515 ||| eng |
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|a books978-3-0365-3027-7
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|a 9783036530260
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|a 9783036530277
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|a Kyamakya, Kyandoghere
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|a Document-Image Related Visual Sensors and Machine Learning Techniques
|h Elektronische Ressource
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| 260 |
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|a Basel
|b MDPI - Multidisciplinary Digital Publishing Institute
|c 2023
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| 300 |
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|a 1 electronic resource (166 p.)
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| 653 |
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|a portable sensor
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|a incomplete multimedia data
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|a multispectral imaging
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| 653 |
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|a Mathematics & science / bicssc
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| 653 |
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|a n/a
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| 653 |
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|a feature learning
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| 653 |
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|a data augmentation
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|a feature selection
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| 653 |
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|a deep learning
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|a house architecture type classification
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| 653 |
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|a document classification
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|a image pre-processing
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| 653 |
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|a perspective correction
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|a house type classification
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| 653 |
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|a image binarization
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| 653 |
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|a local thresholding
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| 653 |
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|a imbalanced dataset
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| 653 |
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|a text position correction
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| 653 |
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|a Research & information: general / bicssc
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| 653 |
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|a encoder-decoder network
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| 653 |
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|a convolutional neural networks
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|a fuzzy c-means
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| 653 |
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|a variational autoencoder
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|a depth image filtering
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| 653 |
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|a visualization
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| 653 |
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|a point clouds filtering
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| 653 |
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|a document images
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| 653 |
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|a chart recognition
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| 653 |
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|a Kinect v2
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| 653 |
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|a scene text recognition
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| 653 |
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|a classification
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| 653 |
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|a detection
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| 653 |
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|a close range
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| 653 |
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|a multiple scales
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| 653 |
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|a scene text detection
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| 653 |
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|a optical character recognition
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| 653 |
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|a hand pose
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| 653 |
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|a natural images
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| 653 |
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|a document scanning
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|a depth resolution
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| 653 |
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|a visual sensor
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| 700 |
1 |
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|a Al-Machot, Fadi
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| 700 |
1 |
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|a Mosa, Ahmad Haj
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| 700 |
1 |
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|a Chedjou, Jean Chamberlain
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
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| 024 |
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|a 10.3390/books978-3-0365-3027-7
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|u https://www.mdpi.com/books/pdfview/book/6885
|7 0
|x Verlag
|3 Volltext
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| 856 |
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|u https://directory.doabooks.org/handle/20.500.12854/98832
|z DOAB: description of the publication
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|a 720
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|a 000
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|a 500
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|a 700
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|a This reprint includes impactful chapters related to document-image related visual sensing, which do present and comprehensively discuss selected scientific concepts, frameworks, architectures and ideas on sensing technologies and machine-learning techniques. Indeed, document imaging/scanning approaches are essential techniques for digitalizing documents in various real-world contexts. This reprint emerging from the Special Issue "Document-Image Related Visual Sensors and Machine Learning Techniques" can be viewed as a result of the crucial need for document management systems. Such technologies are being applied in various fields or different domains and parts of the world to address relevant challenges that could not be addressed without the advances made in these technologies. The reprint includes impactful chapters that present scientific concepts, frameworks, architectures and innovative ideas on sensing technologies and machine-learning techniques to overcome a series of key challenges related to document imaging/scanning, text detection, text recognition, and documents clustering.
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