| Project/Area Number |
14580435
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Konan University |
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Principal Investigator |
WATANABE Eiji Konan University, Faculty of Science and Engineering, Associate Professor, 理工学部, 助教授 (20220866)
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| Co-Investigator(Kenkyū-buntansha) |
ISHIKAWA Hiroshi Fukuyama University, Faculty of Engineering, Research Associate, 工学部, 助手 (90309633)
OZEKI Takashi Fukuyama University, Faculty of Engineering, Lecturer, 工学部, 講師 (40299300)
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| Project Period (FY) |
2002 – 2003
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| Project Status |
Completed (Fiscal Year 2003)
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| Budget Amount *help |
¥3,700,000 (Direct Cost: ¥3,700,000)
Fiscal Year 2003: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2002: ¥2,900,000 (Direct Cost: ¥2,900,000)
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| Keywords | distributed-cooperative processing / PC cluster / image restoration / neural network / region segmentation / autonomous agent / intelligent image processing / dynamic load balancing / 分散・協調型環境 / ディジタル信号処理 / メタレベルアーキテクチャ / 画像処理の知能 / 画像処理 / タスク分割 / 動的分散 / 協調学習法 |
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| Research Abstract |
(1)Intelligent learning of neural networks for image processing :
(a)An image segmentation method using multiple multi-layered neural networks has been newly introduced and an image segmentation method is proposed based on the differences among the compression abilities in multiple NNs. The segmentation results by the proposed method have been concretely shown by some experiments.
(b)A cooperative learning algorithm for multi-layered neural networks is proposed.
The proposed algorithm has the following procedures ; (i)parallel learning of each NN with different initial weights by using the back propagation learning algorithm, (ii)exchange of weights so as to minimize the unbalance among the group of NNs and improve the learning performance of them. We have applied the proposed algorithm for a classification problem of Japanese-Kanji fonts and have shown its behavior and effectiveness.
(2)Image Restoration :
(a)Considering that a partial image which contains some edges tends to become a bina
… More
ry image, we introduced a new evaluation function that takes a maximum for binary images and proposed an automatic extracting method of an edge area from a degraded image using the function.
(b)We discussed the problem to estimate an original image and a point spread function from only a degraded image. We showed that there exist finite solutions if a degraded image has a compact support. Then, we proposed an algorithm to find all solutions.
(3)Considerations on the structure of a distributed and cooperative computational environment :
Our distributed and cooperative computational environment is based on a PC cluster, Unix-like operating systems, and MPI. We proposed a method of the dynamic load balancing on such environment. In the method, we regarded a cluster and a PC cluster system as an autonomous agent and a multi-agent system respectively. The cluster is designed using the meta-level architecture which consists of base level for usual computations and meta level for global computations. According to the method, the dynamic load balancing on such environment is performed as the communication and load balancing on the multi-agent system. Less
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