Results 261 to 270 of about 86,091 (310)

Perturbations of CNNs

Proceedings of IEEE International Symposium on Circuits and Systems - ISCAS '94, 2002
If a CNN template, through the application of one of the sign-changing transformations T defined by Chua and Wu (see Int. Journal of Circuit Theory and Applications, vol. 20, p.497-517, 1992), is positive and cell-linking and has isolated equilibria then the convergence of the original CNN follows; this is theorem 4 of the aforementioned paper.
Mark P. Joy, Vedat Tavsanoglu
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CNN

2023
The field of artificial intelligence (AI) is very promising with the emergence of machine learning and deep learning algorithms. The rise of convolutional neural networks (CNN) is very propitious in deep learning as it is more accurate and powerful than previously known soft computational models like artificial neural networks (ANN) and recurrent ...
Mohan Kumar Dehury, Ronit Kumar Gupta, Tannisha Kundu   +2 more
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Nonlinear CNN: improving CNNs with quadratic convolutions

Neural Computing and Applications, 2019
In this work, instead of designing deeper convolutional neural networks, we investigate the relationship between the nonlinearity of convolution layer and the performance of the network. We modify the normal convolution layer by inserting quadratic convolution units which can map linear features to a higher-dimensional space in a single layer so as to ...
Yiyang Jiang, Fan Yang 0001, Hengliang Zhu, Dian Zhou, Xuan Zeng 0001   +4 more
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MULTIPURPOSE HYSTERESIS CNN

International Journal of Bifurcation and Chaos, 2004
In this paper, we propose a multipurpose hysteresis CNN (cellular neural network) made of first-order cells with hysteresis switches. The hysteresis CNN has applications not only in image processing, but also in pattern formation, nonlinear wave propagation and associative and dynamic memories, because each hysteresis CNN cell has two operating modes,
Makoto Itoh, Leon O. Chua
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HYPERCHAOS IN A SIMPLE CNN

International Journal of Bifurcation and Chaos, 2006
In this paper we demonstrate hyperchaotic dynamics in a very simple Cellular Neural Network (CNN) which is a one-dimensional regular array of four cells. The Lyapunov spectrum is calculated in a range of parameters, and the bifurcation plot is presented as well.
Qingdu Li, Xiao-Song Yang, Fangyan Yang
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SP-CNN: A Scalable and Programmable CNN-Based Accelerator

IEEE Micro, 2015
Specialized accelerators have become prevalent in many mobile computing platforms for their ability to perform certain tasks, such as image processing, at a lower power cost than a generalized CPU or GPU. In this article, the authors focus on using cellular neural networks (CNNs) as a specialized accelerator.
Dilan Manatunga, Hyesoon Kim, Saibal Mukhopadhyay   +2 more
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G-CNN and F-CNN: Two CNN based architectures for face recognition

2017 International Conference on Big Data Analytics and Computational Intelligence (ICBDAC), 2017
In the recent past, deployment of Convolutional Neural Networks (CNN) has led to prodigious success in many pattern recognition tasks. This is mainly due to the very nature of CNN, that is its ability to work in a similar manner to that of the visual system of the human brain.
A Vinay, Desanur Naveen Reddy, Abhishek C. Sharma, S Daksha, N S Bhargav, M K Kiran, K N B Murthy, S Natrajan   +7 more
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CNN-SIM: A Detailed Arquitectural Simulator of CNN Accelerators

2020
In this work we provide a quick overview of our ongoing effort to derive an open-source framework for detailed architectural simulation of the inference procedure of CNN hardware accelerators. Our tool, called CNN-SIM, exposes the values computed during the inference procedure of any CNN model using real inputs, which allows the investigation of ...
Francisco Muñoz-Martínez, José L. Abellán, Manuel E. Acacio   +2 more
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The orthogonal CNN problem

Information Processing Letters, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kazuo Iwama, Kouki Yonezawa
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Image compression by CNN

Proceedings of International Conference on Neural Networks (ICNN'96), 2002
This paper presents a very efficient image compression method well suited to the local nature of the CNN Universal Machine. In the case of lossless image compression it outperforms the JPEG image compression standard both in terms of compression efficiency and speed.
Péter L. Venetianer, Tamás Roska
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