Document-Image Related Visual Sensors and Machine Learning Techniques / / Kyandoghere Kyamakya, [and three others], editors.

• TeilnehmendeR: Kyamakya, Kyandoghere,
• Place / Publishing House: Basel : : MDPI - Multidisciplinary Digital Publishing Institute,, 2023.
• Year of Publication: 2023
• Language: English
• Physical Description: 1 online resource (166 pages)
• ISBN: 3036530274
• Hierarchical level: Monograph
• Statement of Responsibility: Kyandoghere Kyamakya, [and three others], editors.

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.