Background subtraction is one of the most popular methods to detect moving objects in *** this paper,we propose an efficient hierarchical background subtraction method with block-based and pixel-based codebooks(CBs) u...
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Background subtraction is one of the most popular methods to detect moving objects in *** this paper,we propose an efficient hierarchical background subtraction method with block-based and pixel-based codebooks(CBs) using haar-like features for foreground *** the block-based stage,four haar-like features and a block average value,which can be calculated rapidly using integral image and are not sensitive to dynamic background,are used to represent a *** the block-based stage we can remove most of the background without reducing the true positive *** overcome the low precision problem in the block-based stage,the pixel-based stage is adopted to increase the *** results show that our approach can provide faster computation speed compared with that of the present related approaches meanwhile,ensure a high correct detection rate.
The Memetic Algorithm (MA), introduced by Pablo Moscato in 1989, integrates Evolutionary Algorithms with local search methods, enhancing its effectiveness in solving complex optimization problems. This paper provides ...
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ISBN:
(数字)9798350367492
ISBN:
(纸本)9798350367508
The Memetic Algorithm (MA), introduced by Pablo Moscato in 1989, integrates Evolutionary Algorithms with local search methods, enhancing its effectiveness in solving complex optimization problems. This paper provides a comprehensive survey of MA research published in 2019, reviewing 75 selected papers from an initial pool of 112 identified through Google Scholar. The selected papers were categorized into five types: optimization problems (40 papers), image processing (10 papers), parallel processing (5 papers), gene/DNA datasets (4 papers), and other applications (16 papers). The survey highlights MA’s versatility and effectiveness across various domains, particularly its potential for solving complex optimization problems. Key findings include the adaptability of MA for diverse applications, its ongoing relevance in addressing challenging issues, and promising opportunities for combining MA with other algorithms to enhance performance. The paper also emphasizes the significance of MA in fields such as image processing, where it improves patternrecognition and image enhancement, and in bioinformatics, where it optimizes gene selection and genetic algorithms. Despite the extensive study of MA, there remains a significant research gap in non-English literature, particularly in Bahasa, limiting accessibility for Indonesian researchers. This survey aims to bridge this gap by providing valuable insights and encouraging further exploration and application of MA to solve increasingly complex problems. It offers a comprehensive overview that underscores the importance of MA and its potential for future research and innovation.
The aim of this paper is to map the pattern of awards for research degree supervision in institutions in Australia and the United Kingdom. In particular, it explores the scope of such awards, their objectives, the cri...
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The aim of this paper is to map the pattern of awards for research degree supervision in institutions in Australia and the United Kingdom. In particular, it explores the scope of such awards, their objectives, the criteria for nomination, the evidence required to be submitted, the composition of award panels, the criteria for award, and the rewards and conditions attached to success. Marked differences are found between these features in the two systems, which it is argued stem mainly from the fact that in Australia institution-led awards are the norm, while in the UK student-led awards are predominant. In conclusion, it is suggested that, while institution-led awards seem more likely to be effective in identifying, recognising and rewarding exemplary supervision, students can and should have an important role to play and, hence, that optimally all stakeholders should be involved in the awards process.
A feature recognition technique is the intelligent interface of CAD/CAPP. Through extracting and recognizing the tolerance and surface roughness, the design features such asholes, steps and other design features in a ...
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A feature recognition technique is the intelligent interface of CAD/CAPP. Through extracting and recognizing the tolerance and surface roughness, the design features such asholes, steps and other design features in a 3D model of parts, the CAD/CAPP can be combined efficiently, and then the CAD/CAPP/CAM system can be integrated. This technique also helps to shorten the cycle of product development, especially process preparation, and reduce the design cost. In this paper, the 3D model features recognition approaches about boundary pattern matching, volume composition, manufacturing resources, and hybridization method are reviewed, and compared in terms of identifying efficiency, identifying accuracy, identifying flexibility, machinability of features, and utilization of manufacturing resource information in a process environment is conducted on the 3D model feature recognition approaches. The main issues of machining feature recognition of the part model are also discussed, and the direction of future researches in this field is presented. It is pointed out that the development of an efficient, accurate, flexible, automatic and intelligent machining feature recognition system will become an important research topic in the field of computer integrated manufacturing in the future.
Since the introduction of rough sets in 1982 by Professor Zdzislaw Pawlak, we have witnessed great advances in both theory and applications. Rough set theory is closely related to knowledge technology in a variety of ...
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Since the introduction of rough sets in 1982 by Professor Zdzislaw Pawlak, we have witnessed great advances in both theory and applications. Rough set theory is closely related to knowledge technology in a variety of forms such as knowledge discovery, approximate reasoning, intelligent and multiagent system design, knowledge intensive computations .
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