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This research proposes to automate the plate recognition process by installing an IP camera on a road and analyzing the video-feed to capture the vehicles along that road. The contours of the characters in a given plate image are detected, violated and isolated from the parent image. This results to segmented characters. Each of the characters are identified using a k nearest neighbors (kNN) algorithm...
Article is devoted to the system development allowing to restore the volume of the left ventricle of heart, to estimate final systolic and diastolic volumes on the basis of the sequence of MRT-images from a parasternal position of a short axis in the automatic mode. The realized system was built on convolutional neural networks, 500 patients were used for training, for testing 200.
The richest information about different emotional states and thinking styles of the person is carried by signature The signature analysis is one of the most effective and reliable indicator for prediction of personality. As it reveals the true personality which includes fears, honesty and many other individual personality traits. This can happen with the help of few features like underscores below...
The use of computer technology in medical sciences is spreading with technology. The use of computers especially for imaging has become a third eye for physicians. In orthopedic surgeons, after simple roentgenograms for fracture detection, the use of computerized tomography and magnetic resonance has provided great convenience in the detection of fracture, typing, and therefore the appropriate treatment...
Automatic segmentation of the left ventricle (LV) can become a useful tool in echocardiography, for instance to provide automatic ejection fraction measurements or to initialize deformation imaging algorithms. Deep neural networks have recently shown very promising results for improving image classification and segmentation. These methods learn using only a set of input and output data, but require...
Every organism emits energy around it which comprises UV-radiation, EM-radiation, infrared and thermal radiation. This energy around human body represents health condition of the subject under study. These energy fields are called as aura of the body under consideration. Several types of equipments are there to capture such energy. Kirlian camera captures the distribution of energy radiation around...
In most big cities, firearm assault is a common crime. Some state of the art research aim to recognize firearms once they were fired. However, to prevent this type of criminal behavior it is necessary to detect firearms in real time, before they are fired, and maintaining at minimum false alarms. In this paper, we propose a method to detect hand guns by using its shape and real dimensions. The proposed...
Finger vein identification, as an important part in biological feature identification, has been widely used in various fields. The finger vein image shows the vein structure captured under infrared ray. This paper firstly ado pts the principal component analysis (PCA) to extract low-dimension features of vein images; and then constructs a multi-layer neural network classifier based on BP Neural Network,...
This proposed method will give a suggestion for Tuberculosis (TB) diagnosing using Artificial Neural Networks (ANN). Since diagnostic imaging techniques such as x-rays (Radiographs), Magnetic Resonance Imaging (MRI), Computed Tomography (CT) are available, X-ray techniques is widely preferred for edging the image of TB affected area in the chest region. This method is preferred due to its fastness...
This paper describes an artificial neural network (ANN) method that employs a feature-learning algorithm to detect the lumen and MA borders in intravascular ultrasound (IVUS) images. Three types of imaging features including spatial, neighboring, and gradient features were used as the input features to the neural network, and then the different vascular layers were distinguished using two sparse autoencoders...
Automatic identification and recognition of medicinal plant species in environments such as forests, mountains and dense regions is necessary to know about their existence. In recent years, plant species recognition is carried out based on the shape, geometry and texture of various plant parts such as leaves, stem, flowers etc. Flower based plant species identification systems are widely used. While...
Grape constitutes one of the most widely grown fruit crop in the India. Manual observation of experts is used in practice for detection of leaf diseases, which takes more time for further control action. Without accurate disease diagnosis, proper control actions cannot be taken at appropriate time. This is where modern agriculture technique is required to detect and prevent the leaf from different...
Traffic Sign Recognition (TSR) system is a significant component of Intelligent Transport System (ITS) as traffic signs assist the drivers to drive more safely and efficiently. This paper represents a new approach for TSR system using hybrid features formed by two robust features descriptors, named Histogram Oriented Gradient(HOG) features and Speeded Up Robust Features(SURF) and artificial neural...
Breast cancer is the most frequently diagnosed non-skin cancer and the leading cause of cancer-deaths among women. With the advances in digital image processing techniques, it is envisaged that Computer aided diagnosis (CAD) systems can be devised to claim results at par with that of a histopathologist. The inherent assumption of this paper is that image-processing techniques and RBFN can be used...
Traffic Sign Recognition (TSR) system is a vital component of intelligent transport system. It plays an important role by enhancing the safety of the drivers, pedestrians and vehicles as traffic signs provide important information of the traffic environment of the road and assist the drivers to drive more safely and easily by guiding and warning. This paper represents road sign detection and recognition...
Computer-aided schizophrenia diagnosis is a difficult task that has been developing for last decades. Since traditional classifiers have not reached sufficient sensitivity and specificity, another possible way is combining the classifiers in ensembles. In this paper, we take advantage of random subspace ensemble method and combine it with multi-layer perceptron (MLP) and support vector machines (SVM)...
Artificial neural networks (ANN) are one of the dominant learning techniques used in the field of artificial intelligence and have significant assets as their properties imitate the behavior of neurons in human brain. In this paper is presented the research focused on ANN, specifically Multilayer perceptron (MPL) with the aim of detection of human face in the still image. This system was implemented...
In this paper, it is proposed a neural network based on by AutoAssociative Pyramidal Neural Network and their architecture, which uses concepts of receptive fields and autoassociative memory. These concepts are widely used in models of artificial neural networks and were incorporated into model proposed in this work. Furthermore, the proposed neural network also uses the concept of sharing weights...
This paper presents a method used for detection of optic nerve in fundus digital images; for this purpose, initially there is a preprocessing and segmentation of digital images of fundus taken from databases Messidor and Stare in order to stand out the veins and blood vessels of ocular region. The processed image is used in an artificial neural network which has three layers; an input layer with 10000...
One of the most challenging problems in the field of digital image processing is image denoising. When processing medical images, it is of particular relevance to improve the perceived quality of images, while preserving the diagnostically relevant information. This paper investigates the capacity of a neural network framework for medical image denoising. Specifically, the performance of the proposed...
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