A cellular neural network based method for classification of magnetic resonance images: towards an automated detection of hippocampal sclerosis
We present a cellular neuronal network (CNN) based approach to classify magnetic
resonance images with and without hippocampal or Ammon's horn sclerosis (AHS) in the …
resonance images with and without hippocampal or Ammon's horn sclerosis (AHS) in the …
Superpixel segmentation based synthetic classifications with clear boundary information for a legged robot
Y Zhu, K Luo, C Ma, Q Liu, B Jin - Sensors, 2018 - mdpi.com
In view of terrain classification of the autonomous multi-legged walking robots, two synthetic
classification methods for terrain classification, Simple Linear Iterative Clustering based …
classification methods for terrain classification, Simple Linear Iterative Clustering based …
CNN-based algorithm for drusen identification
P Checco, F Corinto - 2006 IEEE International Symposium on …, 2006 - ieeexplore.ieee.org
Drusen characterize the age-related macular degeneration. Automatic procedures for their
identification have been recently developed. In this paper a cellular neural network based …
identification have been recently developed. In this paper a cellular neural network based …
Non‐linear coupled CNN models for multiscale image analysis
A CNN model of partial differential equations (PDEs) for image multiscale analysis is
proposed. The model is based on a polynomial representation of the diffusivity function and …
proposed. The model is based on a polynomial representation of the diffusivity function and …
Variational computing based segmentation methods for medical imaging by using CNN
A Gacsádi, P Szolgay - 2010 12th International Workshop on …, 2010 - ieeexplore.ieee.org
The paper presents a new variational computing based medical image segmentation
method by using Cellular Neural Networks (CNN). By implementing the proposed algorithm …
method by using Cellular Neural Networks (CNN). By implementing the proposed algorithm …
Object comparison using PDE‐based wave metric on cellular neural networks
I Szatmári - International journal of circuit theory and …, 2006 - Wiley Online Library
The paper investigates PDE‐based dynamic phenomena for comparing objects and
introduces a spatio‐temporal non‐linear wave metric. This metric is capable of comparing …
introduces a spatio‐temporal non‐linear wave metric. This metric is capable of comparing …
Modular Cellular Neural Network Structure for Wave‐Computing‐Based Image Processing
This paper introduces the modular cellular neural network (CNN), which is a new CNN
structure constructed from nine one‐layer modules with intercellular interactions between …
structure constructed from nine one‐layer modules with intercellular interactions between …
A method analysis for hail cloudy prediction based on CNN
L Guodong, X Wenxia, Y Bing, B Awudong… - Cluster Computing, 2016 - Springer
A hailstorm forecast method is proposed in the paper. Edge Detect Cellular Neural Network
(EDCNN) method is used to extract the edge of cloud radar images. We have detected the …
(EDCNN) method is used to extract the edge of cloud radar images. We have detected the …
Energy based medical imaging segmentation methods by using Cellular Neural Networks
A Gacsádi, l Ţepelea, I Gavriluţ, O Straciuc - Proceedings of the 15th …, 2011 - dl.acm.org
The paper presents energy based medical imaging segmentation methods by using Cellular
Neural Networks (CNN). By implementing the proposed algorithm on FPGA (Field …
Neural Networks (CNN). By implementing the proposed algorithm on FPGA (Field …