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Automated grading of left ventricular segmental wall motion by an artificial neural network using color kinesis images

L.O. Murta Jr., E.E.S. Ruiz, A. Pazin-Filho, A. Schmidt, O.C. Almeida-Filho, M.V. Simões, J.A. Marin-Neto, B.C. Maciel
2006 Brazilian Journal of Medical and Biological Research  
An artificial neural network (ANN) was developed and validated for grading LV segmental WM using data from color kinesis (CK) images, a technique developed to display the timing and magnitude of global  ...  The present study describes an auxiliary tool in the diagnosis of left ventricular (LV) segmental wall motion (WM) abnormalities based on color-coded echocardiographic WM images.  ...  A multi-layer perceptron neural network was developed and trained in order to provide an automated tool for analysis of regional systolic function using color kinesis images.  ... 
doi:10.1590/s0100-879x2006000100001 pmid:16400459 fatcat:qxmcigbktreh7h7cr55tgbxf3y

Skin Color Detection Model Using Neural Networks and its Performance Evaluation

Bhoyar
2010 Journal of Computer Science  
In this study we present a pixel based skin color classification approach, for detecting skin pixels and non skin pixels in color images, using a novel neural network symmetric classifier.  ...  Ground truth skin segmented images were obtained by using semiautomatic skin segmentation tool developed by the authors.  ...  Here we give a brief review of the neural network models for skin detection. A Multi-Layer Perception (MLP) based skin color model for face detection is proposed by Ming-Jung et al. (2003) .  ... 
doi:10.3844/jcssp.2010.963.968 fatcat:3fczds77czcx7hqnwztyg7a3fe

Digital Image Processing Techniques for Early Detection and Classification of different Diseased Plants

Swati Singh, Sheifali Gupta
2016 International Journal of Bio-Science and Bio-Technology  
The proposed paper surveys different techniques for early spotting and classification of diseased plant using digital image processing.  ...  This paper provides an overview of different image processing techniques and classification methods.  ...  networks for classification 88.5 [10] Corn YcbCr Color Space for segmentation and neural networks for classification 98 [11] Plant Leaf SVM for classification 94.5 [12] Wheat, Grape Neural networks  ... 
doi:10.14257/ijbsbt.2016.8.4.07 fatcat:2wgkmejxpnaz5ciiy4ovxj5kaa

An Adaptive Color Image Segmentation

Deshmukh K.S., Shinde G. N.
2006 ELCVIA Electronic Letters on Computer Vision and Image Analysis  
A novel Adaptive Color Image Segmentation (ACIS) System for color image segmentation is presented.  ...  Here, the main use of neural network is to detect the number of objects automatically from an image. The advantage of this method is that no a priori knowledge is required to segment the color image.  ...  Guterman [13] proposed a neural network based adaptive thresholding segmentation algorithm for monochrome image.  ... 
doi:10.5565/rev/elcvia.115 fatcat:3hutae3jevcbvpmygsa5snor5i

Natural Hand Gestures Recognition System for Intelligent HCI: A Survey

Vishal Nayakwadi, N B Pokale
2013 International Journal of Computer Applications Technology and Research  
A review of static hand posture methods are explained with different tools and algorithms applied on gesture recognition system, including connectionist models, hidden Markov model, and fuzzy clustering  ...  Gesture recognition is to recognizing meaningful expressions of motion by a human, involving the hands, arms, face, head, and/or body.  ...  A colored glove used for input image data, and for segmentation process, HSI color model is applied.  ... 
doi:10.7753/ijcatr0301.1003 fatcat:3yajjs64nfg4jmi2qliibhpkcu

Rice Grains Categorization using Neural Network

Dr. C V lu Narasimhu
2019 International Journal for Research in Applied Science and Engineering Technology  
The steps include image acquisition, image segmentation, feature extraction, neural network classifier and decision making.  ...  In this paper, an algorithm is used to classify three different varieties of rice based on their features. The proposed algorithm is a supervised learning algorithm which consists of five steps.  ...  It consists of following steps: Image Acquisition, Image Segmentation, Feature Extraction, Neural Network Classifier and Classification & Decision.  ... 
doi:10.22214/ijraset.2019.5110 fatcat:sfcheknvmjakpn76blh26lvafe

Survey on Various Gesture Recognition Technologies and Techniques

Noor AdnanIbraheem, Rafiqul Zaman Khan
2012 International Journal of Computer Applications  
Hand gesture is a method of non-verbal communication for human beings for its freer expressions much more other than body parts.  ...  Using gestures as a natural interface benefits as a motivation for analyzing, modeling, simulation, and recognition of gestures.  ...  A colored glove used for input image data, and for segmentation process, HSI color model is applied.  ... 
doi:10.5120/7786-0883 fatcat:vbs2vtzbvfa5ppsdy6kr2kwevy

Model for identification of correct positioning of parts in a pick and place system

Juan Julio Cesar Campas-Buitimea, Samuel González-López, Luis Arturo Medina-Muñoz, Indelfonso Rodriguez-Espinoza
2019 Revista de tecnología e innovación  
The proposed model is based on two stages, one performs detection and the other is for recognition. In the first stage, color segmentation algorithms have been tested.  ...  This article investigates the use of automatic learning classification techniques applied to the task of recognizing the correct shape and color of pieces in a connector using neural networks.  ...  This tool is used to segment the input image data (grayscale or 2D color), TWS transforms the segmentation problem into a pixel classification problem in which each pixel can be classified as belonging  ... 
doi:10.35429/jti.2019.18.6.1.4 fatcat:zl4xy2k375bvfaarawutopukfi

Computer-aided analysis of nuclear stained breast cancer cell images

P. Phukpattaranont, P. Boonyaphiphat
2008 2008 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology  
We present an algorithm for segmenting cells in a microscopic image of immunohistologically stained slides from breast cancer based on color contents.  ...  The procedure for the approach consists of color categorization using neural network, noise removal and shape simplification using mathematical morphology, and cell size consideration.  ...  In this paper, we proposed the use of pixel color partitioning based on a neural network classifier and morphological operators for segmenting cancer cells microscopically.  ... 
doi:10.1109/ecticon.2008.4600476 fatcat:gtbddfvpurc2jamh2gq4rr26hu

Neural Network Based Foreground Segmentation with an Application to Multi-Sensor 3D Modeling

Miti Ruchanurucks, Koichi Ogawara, Katsushi Ikeuchi
2006 2006 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems  
In the case of images captured from a single 2D camera, a hybrid experience-based foreground segmentation technique is developed using a neural network and graph cut paradigm.  ...  This paper presents a technique for foreground/background segmentation using either color images or a combination of color and range images.  ...  A.Hybrid Method Based on its main strength -effectiveness in recognition -a neural network is the basis of this work.  ... 
doi:10.1109/mfi.2006.265586 dblp:conf/mfi/RuchanurucksOI06 fatcat:uptehgghvfgnzpomzratj2g5ru

Analysis of Rice Granules using Image Processing and Neural Network Pattern Recognition Tool

Abirami. S, Neelamegam. P, Kala. H.
2014 International Journal of Computer Applications  
The morphological features extracted from the image are given to Neural Network Pattern Recognition Tool.  ...  In this manuscript, investigation is performed on basmati rice granules; to appraise the act via image processing and Neural Network Pattern Recognition Tool which is implemented based on the features  ...  Neural Network Pattern Recognition Tool is lucratively applied in grading rice granules. The developed Neural Network can be adapted for grading added grains and foodstuffs as well.  ... 
doi:10.5120/16806-6530 fatcat:pkfv7xu2grhyxpzapojvfppb2q

Recent Advances of Deep Learning for Computational Histopathology: Principles and Applications

Yawen Wu, Michael Cheng, Shuo Huang, Zongxiang Pei, Yingli Zuo, Jianxin Liu, Kai Yang, Qi Zhu, Jie Zhang, Honghai Hong, Daoqiang Zhang, Kun Huang (+2 others)
2022 Cancers  
Followed by the discussion of color normalization, we review applications of the deep learning method for various H&E-stained image analysis tasks such as nuclei and tissue segmentation.  ...  Deep learning and its extensions have opened several avenues to tackle many challenging histopathological image analysis problems including color normalization, image segmentation, and the diagnosis/prognosis  ...  Deep Neural Network Deep learning is a new research direction in the field of machine learning based on the deep neural network, which has greatly boosted the performance of natural image The machine learning-based  ... 
doi:10.3390/cancers14051199 pmid:35267505 pmcid:PMC8909166 fatcat:7tfcfh4z45goxbcgf23sncok5a

Neural Style Transfer for Remote Sensing [article]

Maria Karatzoglidi, Georgios Felekis, Eleni Charou
2020 arXiv   pre-print
Neural Style Transfer (NST) constitutes an essential tool for a wide range of applications, such as artistic stylization of 2D images, user-assisted creation tools and production tools for entertainment  ...  The purpose of this study is to present a method for creating artistic maps from satellite images, based on the NST algorithm.  ...  This technique is based on Convolutional Neural Networks (CNN), and more specifically on the VGG-19 neural network architecture, which consists of 5 pooling layers for downsampling and several convolutional  ... 
arXiv:2007.15920v1 fatcat:tyl56kiuojdldgsbn455izstda

Image Segmentation using Learning Vector Quantization of Artificial Neural Network

Hemangi Pujara, Kantipudi MVV
2013 International Journal of Advanced Research in Artificial Intelligence (IJARAI)  
This paper presents color image segmentation application for road-sign detection and recognition system based on Learning vector Quantization (LVQ).  ...  LVQ neural network is used to detect the color from the images and recognize them with high accuracy and speed.  ...  Fig. 8 shows the GUI implementation for color segmentation based on neural network. Using webcam, image is captured and within the short duration of time color is detected using LVQ.  ... 
doi:10.14569/ijarai.2013.020708 fatcat:h6zmsucwpvf4djjiebiwqpquom

Mass Detection in Lung CT Images Using Region Growing Segmentation and Decision Making Based on Fuzzy Inference System and Artificial Neural Network

Atiyeh Hashemi, Abdol Hamid Pilevar, Reza Rafeh
2013 International Journal of Image Graphics and Signal Processing  
Accordingly, this article aim at presenting a method to improve the efficiency of the lung cancer diagnosis system, through proposing a region growing segmentation method to segment CT scan lung images  ...  In the following, this paper is testing the diagnostic performances of FIS system by using artificial neural networks (ANNs).  ...  His fields of interest include Medical Intelligence and Image Processing, 3D Modeling, and Speech and Natural Language Processing.  ... 
doi:10.5815/ijigsp.2013.06.03 fatcat:netv3syvkzfy7dhsv63enqjdaq
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