Edge detection of noisy images based on cellular neural networks

2011 ◽  
Vol 16 (9) ◽  
pp. 3746-3759 ◽  
Author(s):  
Huaqing Li ◽  
Xiaofeng Liao ◽  
Chuandong Li ◽  
Hongyu Huang ◽  
Chaojie Li
Keyword(s):  
Neural Networks ◽  
Edge Detection ◽  
Cellular Neural Networks ◽  
Noisy Images

CELLULAR NEURAL NETWORKS FOR EDGE DETECTION

2007 ◽  
Vol 17 (04) ◽  
pp. 1323-1328
Author(s):  
GIUSEPPE GRASSI ◽  
PIETRO VECCHIO ◽  
EUGENIO DI SCIASCIO ◽  
LUIGI A. GRIECO
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Edge Detection ◽  
Cellular Neural Network ◽  
Cellular Neural Networks ◽  
Detection Technique ◽  
Hardware Implementations ◽  
Rigorous Model ◽  
Better Than

This Letter presents an effective edge detection technique based on the cellular neural network paradigm. The approach exploits a rigorous model of the image contours and takes into account some electrical restrictions of existing hardware implementations. The method yields accurate results, better than the ones achievable by other cellular neural network-based techniques.

Algorithms for segmentation and recognition of objects on medical images based on chiarlet transformation and neural networks

2020 ◽  
pp. 35-45
Author(s):  
Y.A. Hamad ◽  
K.V. Simonov ◽  
A.S. Kents
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Computer Vision ◽  
Edge Detection ◽  
Medical Images ◽  
Classification Algorithms ◽  
Visual Data ◽  
Recognition Of Objects

The paper considers general approaches to image processing, analysis of visual data and computer vision. The main methods for detecting features and edges associated with these approaches are presented. A brief description of modern edge detection and classification algorithms suitable for isolating and characterizing the type of pathology in the lungs in medical images is also given.

New Criteria on Stability of Dynamic Memristor Delayed Cellular Neural Networks

2020 ◽  
pp. 1-13
Author(s):  
Kun Deng ◽  
Song Zhu ◽  
Wei Dai ◽  
Chunyu Yang ◽  
Shiping Wen
Keyword(s):  
Neural Networks ◽  
Cellular Neural Networks ◽  
New Criteria

scholarly journals Existence and exponential stability of a periodic solution for fuzzy cellular neural networks with time-varying delays

2011 ◽  
Vol 21 (4) ◽  
pp. 649-658 ◽  
Author(s):  
Qianhong Zhang ◽  
Lihui Yang ◽  
Daixi Liao
Keyword(s):  
Neural Networks ◽  
Periodic Solution ◽  
Exponential Stability ◽  
Differential Inequality ◽  
Sufficient Conditions ◽  
Coincidence Degree ◽  
Cellular Neural Networks ◽  
Time Varying ◽  
Fuzzy Cellular Neural Networks ◽  
Inequality Technique

Existence and exponential stability of a periodic solution for fuzzy cellular neural networks with time-varying delays Fuzzy cellular neural networks with time-varying delays are considered. Some sufficient conditions for the existence and exponential stability of periodic solutions are obtained by using the continuation theorem based on the coincidence degree and the differential inequality technique. The sufficient conditions are easy to use in pattern recognition and automatic control. Finally, an example is given to show the feasibility and effectiveness of our methods.

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