Neural Networks in Image Processing: A Review of Current Applications
This paper describes current applications of neural networks in image processing. Artificial neural networks (ANNs) are methods of computation and information processing modelled by the brain. Many recent attempts to improve the flexibility and effectiveness of ANNs have focused on the implementatio...
保存先:
| 主要な著者: | , |
|---|---|
| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
INTI Publishing House Sdn. Bhd.
2006
|
| 主題: | |
| オンライン･アクセス: | http://eprints.intimal.edu.my/363/1/2006_7.pdf http://eprints.intimal.edu.my/363/ |
| タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|
| 要約: | This paper describes current applications of neural networks in image processing. Artificial neural networks (ANNs) are methods of computation and information processing modelled by the brain. Many recent attempts to improve the flexibility and effectiveness of ANNs have focused on the implementation level. In this article, we look into ANNs used in the different stages of image processing, specifically in the preprocessing, data reduction, segmentation, object recognition and image understanding phases. The focus is on current and future ANNs, including feed-forward networks, Kohonen feature maps, Hopfleld networks, goal-seeking neuron (GSN) and cellular neural network (CNN). New types of ANNs are fast increasing. Through this survey of introducing the findings, implementations and recent advances of ANNs in Image processing, it is hoped that this paper will serve as a summary, or base to accelerate further development and use of ANN5 in the field of image processing, and improving the accuracy and speed of image processing tasks in the future. |
|---|