TITLE

The dynamic model of lateral inhibition network and it is application

AUTHOR(S)
Feng, Li; Xiaoqiang, Liu
PUB. DATE
May 2013
SOURCE
Neural Computing & Applications;May2013 Supplement, Vol. 22, p125
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Concentrate on the computational model of visual attention, in this paper, we present the electric circuit model of the human retina cells on the base of lateral inhibit network and then deduce the mathematic formulas to define the static and dynamic processes of the network. The learning algorithm is also discussed to get right model parameters. The model reveals the case of the human biological character on image and video processing. Specifically on video processing, the convolution integral function which shows the neural computing process of the human eyes is developed based on the dynamical equation and the circuit principle. Some examples are also introduced to demonstrate the neural computing process of the model on the static image and video processing.
ACCESSION #
87661098

 

Related Articles

  • Region-Based Image Fusion with Artificial Neural Network. Shuo-Li Hsu; Peng-Wei Gau; I.-Lin Wu; Jyh-Horng Jeng // Proceedings of World Academy of Science: Engineering & Technolog;May2009, Vol. 53, p156 

    For most image fusion algorithms separate relationship by pixels in the image and treat them more or less independently. In addition, they have to be adjusted different parameters in different time or weather. In this paper, we propose a region-based image fusion which combines aspects of...

  • Reconstruction and recognition of face and digit images using autoencoders. Tan, Chun; Eswaran, C. // Neural Computing & Applications;Oct2010, Vol. 19 Issue 7, p1069 

    This paper presents techniques for image reconstruction and recognition using autoencoders. Experiments are conducted to compare the performances of three types of autoencoder neural networks based on their efficiency of reconstruction and recognition. Reconstruction error and recognition rate...

  • Challenging the Recognition of Facial Expression via Deep Learning. Dekun Hu; Yonghong Liu; Li Zhang; Guiduo Duan // Applied Mechanics & Materials;2014, Issue 571-572, p717 

    A deep Neural Network model was trained to classify the facial expression in unconstrained images, which comprises nine layers, including input layer, convolutional layer, pooling layer, fully connected layers and output layer. In order to optimize the model, rectified linear units for the...

  • Neural computer searches out tanks.  // Design News;3/25/91, Vol. 47 Issue 6, p55 

    Reports that the Sandia National Laboratories has demonstrated a neural computer program called Feed-Forward Neural Network Pipeline for recognizing tanks regardless of orientation to the camera. Use of multiple processors to screen image pixels and assign weights to them according to a linear...

  • Editorial. MacIntyre, John // Neural Computing & Applications;2001, Vol. 10 Issue 3, p193 

    Editorial. Introduces a series of articles on applied research in the field of neural computing published in the July 2001 issue of the 'Neural Computing & Applications' journal.

  • Editorial. MacIntyre, John // Neural Computing & Applications;2002, Vol. 11 Issue 1, p1 

    Introduces a series of articles dealing with neural computing and applications. Integration of neural works into database technology; Algorithmic and machine learning approaches to the automatic fitting of Gaussian peaks; Self-organizing maps.

  • Practical applications of neural networks. Palade, Vasile; Jain, Lakhmi // Neural Computing & Applications;2005, Vol. 14 Issue 2, p95 

    Introduces a series of articles on issues related to neural computing and applications.

  • Neural computing.  // Management Accounting: Magazine for Chartered Management Account;Apr95, Vol. 73 Issue 4, p30 

    Focuses on neural networks. Elements; Systems analysis; Applications; Management concerns; Risks areas; Recommended project life cycle.

  • Error Concealment Using Adaptive Multilayer Perceptrons (MLPs) for Block-Based Image Coding. Huang, Yu-Len; Chang, Ruey-Feng // Neural Computing & Applications;2000, Vol. 9 Issue 2 

    Image coding algorithms such as Vector Quantisation (VQ), JPEG and MPEG have been widely used for encoding image and video. These compression systems utilise block-based coding techniques to achieve a higher compression ratio. However, a cell loss or a random bit error during network...

Share

Read the Article

Courtesy of VIRGINIA BEACH PUBLIC LIBRARY AND SYSTEM

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics