An immune oriented multi-agent system for biological image processing

Rodin, Vincent; Benzinou, Abdesslam; Guillaud, Anne; Ballet, Pascal; Harrouet, Fabrice; Tisseau, Jacques; Bihan, Jean Le

doi:10.1016/j.patcog.2003.09.014

Cited by 47 publications

(28 citation statements)

References 9 publications

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“…The immune system integrates a wide set of mechanisms: pattern recognition (affinity), clonal selection (cloning the antibodies that best match the antigen), clonal suppression (killing the worst antibodies), mutation (modifying a set of antibodies), affinity maturation (creating a new set of antibodies), learning and memory (storing the successful antibodies). AIA have been successfully used in network security [11], parallel processing [13], image processing [14], robotic [15] and many challenging optimization problems [16].…”

Section: Aiamentioning

confidence: 99%

A multi-objective adaptive immune algorithm for multi-application NoC mapping

Sepulveda

Chau

Gogniat

et al. 2012

Analog Integr Circ Sig Process

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Current SoC design trends are characterized by the integration of larger amount of IPs targeting a wide range of application fields. Such multi-application systems are constrained by a set of requirements. In such scenario network-on-chips (NoC) are becoming more important as the on-chip communication structure. Designing an optimal NoC for satisfying the requirements of each individual application requires the specification of a large set of configuration parameters leading to a wide solution space. It has been shown that IP mapping is one of the most critical parameters in NoC design, strongly influencing the SoC performance. IP mapping has been solved for single application systems using single and multi-objective optimization algorithms. In this paper we propose the use of a multi-objective adaptive immune algorithm (M 2 AIA), an evolutionary approach to solve the multi-application NoC mapping problem. Latency and power consumption were adopted as the target multi-objective functions. To compare the efficiency of our approach, our results are compared with those of the genetic and branch and bound multi-objective mapping algorithms. We tested 11 wellknown benchmarks, including random and real applications, and combines up to 8 applications at the same SoC.The experimental results showed that the M 2 AIA decreases in average the power consumption and the latency 27.3 and 42.1 % compared to the branch and bound approach and 29.3 and 36.1 % over the genetic approach.

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Section: Aiamentioning

confidence: 99%

A multi-objective adaptive immune algorithm for multi-application NoC mapping

Sepulveda

Chau

Gogniat

et al. 2012

Analog Integr Circ Sig Process

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“…The same authors [10] have resumed later the same approach and have extended it by using the multi-agent language oRis. By considering the a priori knowledge on the topology of regions in certain types of images, the agents follow the lines of gradient extremum.…”

Section: Multi-agent Approches For Image Segmentationmentioning

confidence: 99%

“…Most of the methods having used the agent paradigm [1,7,9,10,6] are supervised and consequently they can be applied only to the images for which they were conceived. The method proposed in this paper is unsupervised.…”

Section: Introductionmentioning

confidence: 99%

A Distributed and Collective Approach for Curved Object-Based Range Image Segmentation

Mazouzi

Guessoum

Michel

2009

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

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Abstract.In this paper, we use multi-agent paradigm in order to propose a new method of image segmentation. The images considered in this work are the range images which can contain at once polyhedral and curved objects. The proposed method uses a multi-agent approach where agents align the region borders to the surrounding surfaces which make emerging a collective segmentation of the image. The agents move on the image and when they arrive on the pixels of a region border they align these pixels to their respective surfaces. The resulting competitive alignment allows at once the emergence of the image edges and the disappearance of the noise regions. The test results obtained with real images show a good potential of the new method for accurate image segmentation.

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“…In recent years, a lot of activities have performed in this context. Nowadays, multi agent systems have used in the most industries widely [2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Building Management Systems by Using Hardware Multi Agents: Fuzzy Approach

Naji¹,

Meybodi²,

Moghaddam³

2011

IJCA

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Growing needs of humanity have forced him to use modern technology in all aspects of his life. Intelligent buildings are one of these modern technologies that have great advantages for people. These buildings include a set of integrated and dynamic systems to manage the allocation of resources and facilitate the residents' lives. In this context and due to high speed, reliability and better respond to environmental changes, we simulate such environment using multi agents with fuzzy approach. To do this, we use Matlab and its fuzzy toolbox. The results shows that parallel processing nature in this kind of multi agents improve the speedup of the system.

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An immune oriented multi-agent system for biological image processing

Cited by 47 publications

References 9 publications

A multi-objective adaptive immune algorithm for multi-application NoC mapping

A multi-objective adaptive immune algorithm for multi-application NoC mapping

A Distributed and Collective Approach for Curved Object-Based Range Image Segmentation

Intelligent Building Management Systems by Using Hardware Multi Agents: Fuzzy Approach

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