Results 221 to 230 of about 215,740 (259)

The variable neighborhood CNN

ISCAS 2001. The 2001 IEEE International Symposium on Circuits and Systems (Cat. No.01CH37196), 2002
The cellular neural network (CNN) has been widely used for associative memory. However, it has a problem called indeterminate cell. We describe this problem and propose the variable neighborhood CNN. As a result, we have been able to avoid the problem, and construct a more efficient CNN system for associative memory in simulation.
Michihiro Namba, Shin'ya Takatori, Hiroaki Kawabata, Zhong Zhang   +3 more
openaire   +2 more sources

Quaternion Phase CNN

2018
The main aim of this work is to present a Quaternion Phase Convolutional Neural Network. We encode 3 quaternion phases and its magnitude as an input. Our approach is bio-inspired and is expressed in one mathematical framework. The main result is to obtain a new space feature representation for deep learning which can capture non-trivial equivariant ...
Eduardo Ulises Moya-Sánchez, Sebastián Salazar-Colores, Abraham Sánchez, Ulises Cortés   +3 more
openaire   +2 more sources

The orthogonal CNN problem

Information Processing Letters, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kazuo Iwama, Kouki Yonezawa
openaire   +3 more sources

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
openaire   +1 more source

Decoupled Convolutions for CNNs

Proceedings of the AAAI Conference on Artificial Intelligence, 2018
In this paper, we are interested in designing small CNNs by decoupling the convolution along the spatial and channel domains. Most existing decoupling techniques focus on approximating the filter matrix through decomposition. In contrast, we provide a two-step interpretation of the standard convolution from the filter at a single ...
Guotian Xie, Ting Zhang 0002, Kuiyuan Yang, Jianhuang Lai, Jingdong Wang 0001   +4 more
openaire   +1 more source

CNN: A Vision of Complexity

International Journal of Bifurcation and Chaos, 1997
CNN is an acronym for either Cellular Neural Network when used in the context of brain science, or Cellular Nonlinear Network when used in the context of coupled dynamical systems. A CNN is defined by two mathematical constructs: 1. A spatially discrete collection of continuous nonlinear dynamical systems called cells, where information can be ...
openaire   +2 more sources

Assamese document classification using CNN, multi-channel CNN and CNN-SVM

AIP Conference Proceedings, 2023
Chayanika Talukdar, Shikhar Kumar Sarma
openaire   +1 more source

Crack Detection and Comparison Study Based on Faster R-CNN and Mask R-CNN

Sensors, 2022
Hao Yang, Peixin Shi, Xiaojun Wei
exaly  

CNN Variants for Computer Vision: History, Architecture, Application, Challenges and Future Scope

Electronics, 2021
Kirit Modi, Chirag I Patel, Hemant Ghayvat   +2 more
exaly  

GH-CNN: A New CNN for Coherent Hierarchical Classification

2022
Mona-Sabrine Mayouf, Florence Dupin de Saint-Cyr   +1 more
openaire   +1 more source