The Potential of the SP System in Machine Learning and Data Analysis for Image Processing
This paper aims to describe how pattern recognition and scene analysis may with advantage be viewed from the perspective of the SP system (meaning the SP theory of intelligence and its realisation in the SP computer model (SPCM), both described in an appendix), and the strengths and potential of the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Big Data and Cognitive Computing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-2289/5/1/7 |
| _version_ | 1797395594959912960 |
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| author | J. Gerard Wolff |
| author_facet | J. Gerard Wolff |
| author_sort | J. Gerard Wolff |
| collection | DOAJ |
| description | This paper aims to describe how pattern recognition and scene analysis may with advantage be viewed from the perspective of the SP system (meaning the SP theory of intelligence and its realisation in the SP computer model (SPCM), both described in an appendix), and the strengths and potential of the system in those areas. In keeping with evidence for the importance of information compression (IC) in human learning, perception, and cognition, IC is central in the structure and workings of the SPCM. Most of that IC is achieved via the powerful concept of SP-multiple-alignment, which is largely responsible for the AI-related versatility of the system. With examples from the SPCM, the paper describes: how syntactic parsing and pattern recognition may be achieved, with corresponding potential for visual parsing and scene analysis; how those processes are robust in the face of errors in input data; how in keeping with what people do, the SP system can “see” things in its data that are not objectively present; the system can recognise things at multiple levels of abstraction and via part-whole hierarchies, and via an integration of the two; the system also has potential for the creation of a 3D construct from pictures of a 3D object from different viewpoints, and for the recognition of 3D entities. |
| first_indexed | 2024-03-09T00:36:46Z |
| format | Article |
| id | doaj.art-b41e2ab13a654246aa3760d9d257ac52 |
| institution | Directory Open Access Journal |
| issn | 2504-2289 |
| language | English |
| last_indexed | 2024-03-09T00:36:46Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Big Data and Cognitive Computing |
| spelling | doaj.art-b41e2ab13a654246aa3760d9d257ac522023-12-11T18:06:01ZengMDPI AGBig Data and Cognitive Computing2504-22892021-02-0151710.3390/bdcc5010007The Potential of the SP System in Machine Learning and Data Analysis for Image ProcessingJ. Gerard Wolff0CognitionResearch.org, 18 Penlon, Menai Bridge, Anglesey LL59 5LR, UKThis paper aims to describe how pattern recognition and scene analysis may with advantage be viewed from the perspective of the SP system (meaning the SP theory of intelligence and its realisation in the SP computer model (SPCM), both described in an appendix), and the strengths and potential of the system in those areas. In keeping with evidence for the importance of information compression (IC) in human learning, perception, and cognition, IC is central in the structure and workings of the SPCM. Most of that IC is achieved via the powerful concept of SP-multiple-alignment, which is largely responsible for the AI-related versatility of the system. With examples from the SPCM, the paper describes: how syntactic parsing and pattern recognition may be achieved, with corresponding potential for visual parsing and scene analysis; how those processes are robust in the face of errors in input data; how in keeping with what people do, the SP system can “see” things in its data that are not objectively present; the system can recognise things at multiple levels of abstraction and via part-whole hierarchies, and via an integration of the two; the system also has potential for the creation of a 3D construct from pictures of a 3D object from different viewpoints, and for the recognition of 3D entities.https://www.mdpi.com/2504-2289/5/1/7information compressionSP-multiple-alignmentpattern recognitionscene analysisparsing |
| spellingShingle | J. Gerard Wolff The Potential of the SP System in Machine Learning and Data Analysis for Image Processing Big Data and Cognitive Computing information compression SP-multiple-alignment pattern recognition scene analysis parsing |
| title | The Potential of the SP System in Machine Learning and Data Analysis for Image Processing |
| title_full | The Potential of the SP System in Machine Learning and Data Analysis for Image Processing |
| title_fullStr | The Potential of the SP System in Machine Learning and Data Analysis for Image Processing |
| title_full_unstemmed | The Potential of the SP System in Machine Learning and Data Analysis for Image Processing |
| title_short | The Potential of the SP System in Machine Learning and Data Analysis for Image Processing |
| title_sort | potential of the sp system in machine learning and data analysis for image processing |
| topic | information compression SP-multiple-alignment pattern recognition scene analysis parsing |
| url | https://www.mdpi.com/2504-2289/5/1/7 |
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