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检索条件"任意字段=Conference on Applications of Artificial Neural Networks in Image Processing II"

共 2695 条记录，以下是1801-1810 订阅

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Automated recognition of lesions in retinal images using artificial neural networks

Automated recognition of lesions in retinal images using art...

引用

IEEE Signal processing and Communications applications (SIU)

作者： Osman Şirvan Atilla Özgür Bilgisayar Mühendisliği Bölümü Ege Üniversitesi Turkey Elektrik ve Elektronik Mühendisliği Bölümü BAŞKENT Üniversitesi Turkey

This study presents an automatic recognition system for different disease lesions (hard exudate (HE), hemorrhage (HMR), microaneurysm (MA), soft exudate (SE) and non-lesion (normal, vessel, optic disc, macula) (N) patterns in retinal images. Proposed method consists of thresholding, morphological operations, filtering, image enhancement, optic disc and macula localization, segmentations, optic disc and vessel elimination, region growing, classification and recognition for four different disease lesions and non-lesion patterns. artificial neural networks (ANNs), Support Vector Machines (SVM) and Radial Basis Function (RBF) were used as classifier to recognize. The features are extracted from the images and fed to input of the ANN. Results were compared with expert ophthalmologists' hand-drawn ground-truth. Experimental results obtained were presented and recognition performances of the system for Multi-Layer Perceptron (MLP), Radial Basis Function (RBF) and Support Vector Machines (SVM) classifiers were compared and discussed.

关键词： Retina Support vector machines Optical imaging Biomedical optical imaging Lesions image recognition

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Prediction of meteorological images based on relaxation labeling and artificial neural network from a given sequence of images

Prediction of meteorological images based on relaxation labe...

引用

International conference on Computer Communication and Informatics (ICCCI)

作者： Amitava Mukhopadhyay Bipasha Paul Shukla Diptiprasad Mukherjee Bhabatosh Chanda ECS Unit Indian Statistical Institute Kolkata India Atmospheric Sciences Division Space Applications Centre ISRO Ahmedabad India

In this paper an algorithm to predict the spectral signature of the short-term evolution of cloud formations using image sequences acquired from ISRO meteorological satellite (Kalpana-1) is described. The proposed algorithm consists of four steps: first step perform image processing activities (thresholding and relaxation); the second step is dedicated to determination of neural net for each pixel in each and every images. The third and fourth step consists of a novel neural network based training and prediction respectively. The main goal of this work is to maximize the prediction accuracy. Various kind of predictions are made depending upon number of feature vectors and number of net used. Mean Square Error is used to evaluate the performance of the neural net and PSNR is used to judge the accuracy of predicted image. Some experimental results obtained by using real image sequences acquired from ISRO meteorological satellite are shown that are extreamly encouraging.

关键词： Vectors Satellites Clouds artificial neural networks Meteorology Neurons

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Breast cancer classification using moments

Breast cancer classification using moments

引用

IEEE Signal processing and Communications applications (SIU)

作者： Alaa Eleyan Electrical & Electronic Engineering (Video Image & Speech Processing Laboratory) Selçuklu Konya TURKEY

This paper presents a system for detecting breast cancer based on moments. Instead of trying to improve the applied classifier we focused on improving the input attributes. We extracted new features from database samples using the first four moments namely, mean, variance, skewness and kurtosis. Through simulations, 10-fold cross validation method was applied to the Wisconsin breast cancer database to evaluate the classification performances. Various classifiers were used for evaluating the proposed approach. Results indicate advantage of such features in improving classification performance for all of the applied classifiers.

关键词： Breast cancer Databases Feature extraction Support vector machine classification artificial neural networks

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Gathering information realtime and anywhere (GIRA) using an ANN algorithm

Gathering information realtime and anywhere (GIRA) using an ...

引用

IEEE International conference on System Engineering and Technology

作者： Aciek Ida Wuryandari Rifki Wijaya School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

By using mobile technology applications and content based image retrieval are integrated with Location Based Services, created an app called "Actual Mobile Application for Tourist Guide" that can be used as a guide in realtime and actual tourists and can also be used as an alternative media for the promotion or advertisements from companies engaged in tourism, such as hotels, restaurants, or travel agent. This application has the potential to be a killer application in the world of mobile applications. The handset is a smart phone that is used with the Windows Phone OS. On the handset will be there making frames for processing in realtime using the SIFT algorithm is then processed using an algorithm ANN (artificial neural Network) to finally matching it with the existing ANN results on mobile phones as well as on the server. First Mobile will detect its presence by using GPS. Once detected the place, it will be given training outcomes data from the database to the phone, according to the radius of the place of its existence.

关键词： Mobile communication artificial neural networks Servers Databases Telephone sets Cameras Mobile computing

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An intelligent reflective colour sensor system for paper and textile industries

An intelligent reflective colour sensor system for paper and...

引用

International conference on Sensing Technology, ICST

作者： P Anupama K V Sathees Kumar S Rominus Valsalam G Harikrishnan V Muralidharan Control and Instrumentation Group Centre for Development of Advanced Computing Thiruvananthapuram Kerala India Control and Instrumentation Group Centre for Development of Advanced Computing (CDAC-T) Thiruvananthaouram Kerala India Centre for Development of Advanced Computing Juhu Maharashtra IN Centre for Development of Advanced Computing (CDAC) Hyderabad Andhra Pradesh India

The world is simply less colorful, without the sense of colour. In ordinary life, a difference in colour perception is mostly inconsequential. However, in many industries, the ability to sense colour precisely can be crucial. In this paper, a novel reflective colour sensing system is presented for process monitoring and control applications in paper and textile industries. The system is developed using a solid state RGB sensor and a smart signal processing algorithm implemented on micro-controller architecture. A hybrid neural network comprising Self organizing mapping and Back propagation architecture is used for colour zone classification and exact colour identification of papers. Demonstrator applications and simulation results are discussed to highlight the importance of sensor and accuracy in measurement.

关键词： Color image color analysis Sensors Neurons artificial neural networks Process control

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Design of a neural Network for a Concentrated Acid Hydrolysis of Biomass in Bioethanol Production as a Clean Energy

Design of a Neural Network for a Concentrated Acid Hydrolysi...

引用

International conference on artificial Intelligence and image processing(ICAiiP’2012);International conference on Innovations in Electrical and Electronics Engineering(ICIEE’2012);International conference on Mechanical,Automobile and Biodiesel Engineering(ICMABE’2012);International conference on History,Literature and Management(ICHLM’2012);International conference on Agriculture,Chemical and Environmental Sciences(ICACES’2012);International conference on Biological and Medical applications(ICBMA’2012)

作者： Ali Arasteh Nodeh Department of Engineering Quchan BranchIslamic Azad University

Application of neural network for modeling the saccharification of biomass by concentrated acid hydrolysis has been *** to a more complex and unknown kinetics of the investigated reaction,the proposed approach based on application of neural networks is an efficient and accurate tool to solve modeling *** Influence of the main pretreatment variables including temperature,processing time,solid contents,and acid concentration on fermentable sugar generation was *** for pretreatment temperature (65,80,90oC),process time (120,180,240 minute),solid content (5,10,15%) and concentration of sulfuric acid (20,40,60%) were *** were analyzed by HPLC and modeled by two layers neural network with different *** layers neural network with different neurons was *** using simple data and a simple neural network,high accuracy was *** trained MLP that has one hidden layer with 11 Log-sig neurons has a lower average relative error for test ***,it is selected as the most suitable network to simulate the concentrated acid hydrolysis process.

关键词： biomass,glucose,Acid sulfuric,concentrated acid hydrolysis,neural network

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Comparison of remote sensing approach for mangrove mapping over Penang Island

Comparison of remote sensing approach for mangrove mapping o...

引用

International conference on Computer and Communication Engineering, ICCCE

作者： Beh Boon Chun Mohd. Zubir Mat Jafri Lim Hwee San School of Physics Universiti Sains Malaysia Minden Penang Malaysia

Mangrove mapping is crucial for the policy maker to have more proper planning of land use of a country or nation while helping to preserve the mangrove area. The unique mangrove ecosystem need to be conserved as mangrove trees has many applications for human being not only in their forestry products such as timber and charcoal but also serve as a strong barrier from the attack of wave, erosion and tsunami to inland area near the seashore or coastal region. The aim of this paper is to compare the accuracy of the mangrove map produced from different remote sensing techniques. Thailand Earth Observation System (THEOS) satellite data of Penang Island with date 29 January 2010 was utilized for the image processing analysis. All the pre-processing, classification, validation and post-classification analysis were done by using Geomatica version 10.3.2 software package. The results obtained show that artificial neural Network (ANN) with classification accuracy of 93.5% can increase the overall accuracy by 2.0% as compare to Maximum Likelihood Classification method (91.5%). This study indicates that ANN approach which has the highest accuracy and kappa coefficient is more reliable used for mangrove mapping at generic level.

关键词： Accuracy Remote sensing artificial neural networks Vegetation mapping Satellites Earth

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Anomaly Based Intrusion Detection for a Biometric Identification System using neural networks

Anomaly Based Intrusion Detection for a Biometric Identifica...

引用

作者： Tinny Mgabile Ishmael S.Msiza Erick Dube the CSIR Modeling & Digital Science the Faculty of Engineering & the Built Environment University of Johannesburg

This manuscript presents a supervised machine learning approach in the identification of network attacks on a fingerprint biometric *** reduce the problem of malicious acts on a biometric system,this manuscript proposes an intrusion detection technique that analyses the fingerprint biometric network traffic for evidence of *** neural network algorithm that imitates the way a human brain works is used in this study to classify normal traffic and learn the correct traffic pattern on a fingerprint biometric *** aim of the study is to observe the ability of the neural network in the detection of known and unknown attacks without using a vast amount of training *** results of the neural network model had a classification rate of 98 %,which translates to a false positive rate of 2%.

关键词： biometric system,neural network,machine learning,intrusion detection.

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Automatic person identification system using handwritten signatures

Automatic person identification system using handwritten sig...

引用

International conference on Computer and Communication Engineering, ICCCE

作者： A.A.M. Abushariah T.S. Gunawan J. Chebil M.A.M. Abushariah ECE Department Faculty of Engineering International Islamic University Malaysia Kuala Lumpur Malaysia Department of Computer Information Systems King Abdullah II School for Information Technology University of Jordan Amman Jordan

This paper reports the design, implementation, and evaluation of a research work for developing an automatic person identification system using hand signatures biometric. The developed automatic person identification system mainly used toolboxes provided by MATLAB environment.. In order to train and test the developed automatic person identification system, an in-house hand signatures database is created, which contains hand signatures of 100 persons (50 males and 50 females) each of which is repeated 30 times. Therefore, a total of 3000 hand signatures are collected. The collected hand signatures have gone through pre-processing steps such as producing a digitized version of the signatures using a scanner, converting input images type to a standard binary images type, cropping, normalizing images size, and reshaping in order to produce a ready-to-use hand signatures database for training and testing the automatic person identification system. Global features such as signature height, image area, pure width, and pure height are then selected to be used in the system, which reflect information about the structure of the hand signature image. For features training and classification, the Multi-Layer Perceptron (MLP) architecture of artificial neural Network (ANN) is used. This paper also investigates the effect of the persons' gender on the overall performance of the system. For performance optimization, the effect of modifying values of basic parameters in ANN such as the number of hidden neurons and the number of epochs are investigated in this work. The handwritten signature data collected from male persons outperformed those collected from the female persons, whereby the system obtained average recognition rates of 76.20% and74.20% for male and female persons, respectively. Overall, the handwritten signatures based system obtained an average recognition rate of 75.20% for all persons.

关键词： Feature extraction artificial neural networks Testing Training Accuracy Databases Computer architecture

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image Receptive Fields neural networks for Object Recognition

引用

21st International conference on artificial neural networks, ICANN 2011

作者： Daum, Pamela Buessler, Jean-Luc Urban, Jean-Philippe Univ Haute Alsace Mulhouse France

ISBN: (纸本)9783642217371;9783642217388

This paper extends a recent and very appealing approach of computational learning to the field of image analysis. Recent works have demonstrated that the implementation of artificial neural networks (ANN) could be simplified by using a large amount of neurons with random weights. Only the output weights are adapted, with a single linear regression. Supervised learning is very fast and efficient. To adapt this approach to image analysis, the novelty is to initialize weights, not as independent random variables, but as Gaussian functions with only a few random parameters. This creates smooth random receptive fields in the image space. These image Receptive Fields - neural networks (IRF-NN) show remarkable performances for recognition applications, with extremely fast learning, and can be applied directly to images without pre-processing.

关键词： artificial neural networks image processing classification extreme learning machine echo state networks image receptive fields

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