Ann artificial neural network based automated coin. Pdf blood cell identification using emotional neural. Credit scoring and evaluation is one of the key analytical techniques in credit risk evaluation which has been an active research area in. Experimental results suggest that artificial emotions can be successfully modeled and efficiciently implemented to improve neural networks. Missing data imputation and neural network application to computational politics.
An intelligent coin identification system that uses coin patterns for. Member, centre of innovation for artificial intelligence email. However, rotated objects may cause incorrect identification by recognition systems. Two neural networks are investigated and a comparison between these networks is drawn.
We propose that neural networks can be trained to establish the nonlinear relationship between the image intensity and its compression ratios in search for an optimum ratio. For the neural network to have a better performance there is a need to transform the attributes values into. Download recent advances in artificial life full book in pdf, epub, a. One of the major factors that cause this increase, is misdiagnoses on the part of medical doctors or ignorance on the part of the patient. We train and implement the neural network to decide whether to approve or reject a credit application, using seven learning schemes and real world credit applications from the australian credit approval datasets. Request pdf neural networks for credit risk evaluation.
Credit rating analysis with support vector machines and neural networks. In section 3, the neural network implementation, experimental results, and performance evaluation are provided, and finally in section 4 the work in this paper is concluded. Khashman is with final international university, girne, mersin 10, turkey. Citeseerx document details isaac councill, lee giles, pradeep teregowda. Procedia computer science 108c 2017 2358a2362 2359 nondestructive prediction of concrete compressive strength using neural networks adnan khashman1 and pinar akpinar 2 1final international university, faculty of engineering, girne, mersin 10 turkey. Arbitration of turkish agricultural policy impact on co2. Heart diseases diagnosis using neural networks arbitration. Pdf image compression using neural networks and haar wavelet. The proposed system was developed and implemented using 100 images of various objects, contrasts and intensities, and two neural networks. During 19982001 he was an assistant professor and chairman of the computer engineering.
Blood cell identification using emotional neural networks citeseerx. Artificial neural networks are computational networks which attempt to. This paper present artificial neural network and support vector machine models as decision. The modelling of these biological processes in machines is considered a challenging and often controversial t. Procedia computer science 102 2016 617 622 619 where, seg is the segment index, p is the pixel value and d is the total number of pixels per segment. Emotional processes and responses are biological and psychological processes in humans. A modified back propagation learning algorithm with added emotional coefficients. Blood cell identification using a simple neural network. Read online recent advances in artificial neural networks epub. Multiexpression face recognition using neural networks and. Neural network, pattern recognition, image processing. The neural network comprises an input layer with 272 neurons that carry the values of the averaged features, a hidden layer with 65 neurons and an output layer with 30 neurons which is the number of persons.
Pdf nondestructive prediction of concrete compressive strength. Investigation of different neural models and learning schemes. Citeseerx image compression using neural networks and. The goal of this journal is to provide a platform for academicians, researchers and practitioners all over the world to promote, share, and discuss various new issues and developments in all areas of control systems and robotics.
Application of an emotional neural network to facial. The aim of an optimum ratio is to combine high compression ratio with good quality compressed image. Deformed banknote identification using pattern averaging and. Icis uses pattern averaging and neural network for recognition of. S tp tp d x y 3 where, tp is the x and y dimension of the image and s is the total number of segments10,16.
Artificial neural networks have been used to solve many problems obtaining outstanding results in various application areas such as power systems. Intelligent systems research group isrg, near east university, lefkosa, mersin 10, turkey. During 19982001 he was an assistant professor and chairman of the computer engineering department, near east university, lefkosa, turkey. Near east university, lefkosa,mersin 10,turkey, member, centre of innovation for artificial intelligence. A neural network will be trained to establish the nonlinear relationship between the image intensity and its compression ratios in. Pdf coin identification using neural networks prof. Intelligent recognition of chelonioidea sea turtles. The ann64 neural network within the image compression system learnt to associate the. Blood cell identification using emotional neural networks. We train and implement three neural networks to decide whether to approve or reject a credit application. In total, there are 6960 values 435 instances x 16 attributes in the dataset. Voltage instability detection using neural networks.
Experimental results show that the additional emotional parameters and weights improved the identification rate as well as the classification time. The 20 training images are of rotated coins at 0 o, 90 o, 180 o and 270 o degrees resulting in 8 4 obverse and 4 reverse 1tl coin images and 12 4 obverse, 4 reverse of italy and 4 reverse of finland. Studies intelligent research systems, face recognition, and moving object recognition. The modifed algorithm, namely the emotional bp learning algorithm, has two emotional parameters, anxiety and confidence, that are modeled during machine learning and decision making. The particular success of neural networks in pattern recognition and therefore character recognition is laudable. It should be noted that the normalization process is applied for. Adnan khashman, self employed, european centre for research and academic affairs ecraa, department member. Neural network applications have lately become a common feature with varying degrees of. Oyebade oyedotun universite du luxembourg academia. Prof dr adnan khashman committee chairman, electrical and electronic engineering, fiu. A rotation invariant intelligent coin identificatiom system icis has been presented by adnan khashman et al. Intelligent prediction of concrete carbonation depth using neural networks. This paper presents a face recognition system that uses eyes, nose and mouth approximations for training a neural network to recognize faces in different expressions such as natural, smiley, sad and surprised.
Application of an emotional neural network to facial recognition. Rotated coin recognition using neural networks springerlink. Journal of information science and engineering 25, 17371751 2009 blood cell identification using emotional neural networks adnan khashman intelligent systems research group isrg faculty of engineering near east university lefkosa, mersin 10, turkey the idea of machines having emotions sounds like science fiction, however, few decades ago the idea of machines with intelligence. Image compression using neural networks and haar wavelet core. Pdf diabetic retinopathy diagnosis using neural network. Multibanknote identification using a single neural network. This study aims to investigate the feasibility of artificial neural networks. Artificial neural networks may probably be the single most successful. This paper presents a credit risk evaluation system that uses a neural network model based on the back propagation learning algorithm. Face recognition using neural networks and pattern averaging. International journal of control systems and robotics iaras. Emotion modeling in neural networks professor adnan khashman founder and head of intelligent systems research group isrg faculty of engineering, near east university nicosia, n.
Also, he is the founding director of the european centre of research and academic affairs ecraa, lefkosa, mersin10, turkey. Citeseerx image compression using neural networks and haar. Proceedings of the 2 nd international symposium on electrical, electronic and computer engineering, neucee 2004, ieee turkey section, nicosia, march 2004, pp. Prototype incorporated emotional neural network piemnn. Neural network is widely used tool for predicting heart disease diagnosis. Index termsigbo vowels character, neural network,recognition. The superiority of the embp, in correct classification rate and speed, when compared to the bp is attributed to the. Pdf heart diseases diagnosis using neural networks.
We propose that neural networks can be trained to establish the nonlinear relationship between the image. Investigation of different neural models and learning schemes a khashman expert systems with applications 37 9, 62336239, 2010. Automatic detection of military targets utilising neural. Zeliha khashman and adnan khashman procedia computer science 102 2016 611 616 6 xmissing value. Neural networks are investigated for predicting the magnitude of the largest seismic event in the following month based on the analysis of eight mathematically. Adnan khashman at european centre for research and academic affairs. Waveletbased image compression provides substantial improvements in picture quality at higher compression ratios. Oyebade oyedotun1, adnan khashman2, gideon joseph3. Nondestructive prediction of concrete compressive strength using. Fuzzy minamax neural networks for categorical data application to missing data imputation. A neural network model for credit risk evaluation pubmed. Neural networks have been used in the development of intelligent recognition systems that simulate our ability recognize patterns.
An emotional system with application to blood cell type. The novelty of our work is the use of voltage output images as the input patterns to the neural network for training and generalizing purposes, thus providing a faster instability detection system that simulates a trained operator controlling and monitoring the 3phase voltage output of the simulated pds. Deep learning in character recognition considering pattern. Citeseerx coin identification using neural networks. Nadire cavus we certify this thesis is satisfactory for the award of the degree of masters of science in civil engineering examining committee in charge. An image compression approach using wavelet transform and. An emotional system with application to blood cell type identification.
Face recognition using neural networks and pattern. Adekunle, temitope odekuoye, adnan khashman, automatic system for grading banana using glcm texture feature extraction and neural network arbitrations, journal of food process engineering, 10. The novel idea is based on combining neural network arbitration and scale space analysis to automatically select one optimum scale for the entire image at which object edge detection can be applied. Procedia computer science 102 2016 583 587 585 design. An artificial neural network ann mimics the structure and function of a biological brain. Pdf image compression using neural networks and haar. This paper suggests that a neural network could be trained to recognize an optimum ratio for haar wavelet compression of an image upon presenting the image to the network. The neural networks are trained using real world credit application cases. Nondestructive prediction of concrete compressive strength.
The international journal of control systems and robotics is an open access journal. Investigation of different neural models and learning schemes adnan khashman 1 sep 2010 expert systems with applications, vol. For training the designed neural network, 30 images of 256 pixels each per class are used. Training parameters of the back propagation network with the best found numbers of hidden neurons are shown in table 1. The neural network is trained using only 20 coin images of the available 120 coin images. Identification of noisy poultry portion images using a neural network 77. We train and implement the neural network to decide whether to approve or reject a. Neurowavelet based efficient image compression using. Such tasks are often assigned to an artificial neural network ann model to arbitrate as they. There is an increase in death rate yearly as a result of heart diseases. Coin identification by machines relies currently on the assessment of the physical parameters of a coin. Coin identification using neural networks request pdf. A reallife application will be presented throughout recognizing the faces of 30 persons. Zeliha khashman and adnan khashman procedia computer science 102 2016.
This paper present artificial neural network and support vector machine models as decision support in classifying processed medical images of the iris, which can significantly raise the. Journal of information science and engineering 25, 17371751 2009 blood cell identification using emotional neural networks adnan khashman intelligent systems research group isrg faculty of engineering near east university lefkosa, mersin 10, turkey the idea of machines having emotions sounds like science fiction, however, few decades ago the idea of machines with intelligence seemed also. Neural network model nn1 nn2 nn3 nn4 nn5 nn6 input layer nodes 14 14 14 14 14 14 hidden layer nodes 10. Adnan khashman et al have proposed a technique for image compression using neural networks and haar wavelet where authors claims that after presenting the image to the network, a backpropagation neural network bpnn could be trained to recognize an optimum ratio for haar wavelet compression of an image. May 28, 2006 this paper introduces a novel approach to face recognition by simulating our ability to recognize familiar faces after a quick glance using pattern averaging and neural networks.
Intelligent grading system for banana fruit using neural. Neural networks combined with image processing can provide sufficient solutions to problems where. Anticipation of political party voting using artificial. Neural networks have been used in the development of intelligent systems that simulate pattern recognition and object identification. The explosive growth in decisionsupport systems over the past 30 years has yielded numerous intelligent systems that have often produced lessthanstellar. Image compression using neural networks and haar wavelet. This paper investigates the efficiency of an emotional neural network, which uses a modified back propagation learning algorithm. Sep 27, 2006 face recognition systems have been investigated while developing biometrics technologies. Dataset normalization and coding dataset coding is an essential and a vital process in designing any intelligent system using neural networks. Adnan khashman, oyebade oyedotun, and olaniyi ebenezer. The performances of the emnn and a conventional bpbased neural network, using two topologies for each network, will be compared when applied to a blood cell type identification problem. Two neural networks receiving different input image sizes are developed in this work and a comparison between their. This paper describes a credit risk evaluation system that uses supervised neural network models based on the back propagation learning algorithm. This requirement is necessary when using neural networks since every neuron within the entire network is designed to receive values between 0 and 1 khashman, 2006.
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