Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.785368
Title: Object detection, recognition and classification using computer vision and artificial intelligence approaches
Author: Matroushi, Gharib Ismail Al
ISNI:       0000 0004 7970 8908
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2018
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Abstract:
Object detection and recognition has been used extensively in recent years to solve numerus challenges in different fields. Due to the vital roles they play, object detection and recognition has enabled quantum leaps in many industry fields by helping to overcome some serious challenges and obstacles. For example, worldwide security concerns have drawn the attention and stimulated the use of highly intelligent computer vision technology to provide security in different environments and in diverse terrains. In addition, some wildlife is at present exposed to danger and extinction worldwide. Therefore, early detection and recognition of potential threats to wildlife have become essential and timely. The extent of using computer vision and artificial intelligence to convert the seemingly insecure world to a more secure one has been widely accepted. Such technologies are used in monitoring, tracking, organising, analysing objects in a scene and for a number of other countless purposes.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.785368  DOI: Not available
Keywords: Information and Computing Sciences not elsewhere classified ; Road surface type recognition ; Airborne industrial dust particle classification ; Camel head detection and recognition ; Deep learning ; K-means ; Machine learning ; Computer vision ; Autonomous vehicles
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