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The Network Function Placement (NFP) problem involves placing Virtual Network Functions (VNFs) in a network in order to meet the Service Function Chain (SFC) requirements of the flows through the network. Simultaneously, the usage of network resources by the VNF instances must be optimized. Prior work primarily treated this as a constraint satisfaction problem, using linear programming to find optimal...
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...
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...
Fuzzy TOPSIS with linguistic assessments is well suited to model the new product design process for describing the relationship between the product form and consumers' preferences, where consumers' preferences are often expressed subjectively and imprecisely. In this paper, we build a Fuzzy TOPSIS expert system in conjunction to a neural network model that can help product designers determine the...
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...
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...
Traffic safety is an important problem for autonomous vehicles. The development of Traffic Sign Recognition (TSR) dedicated to reducing the number of fatalities and the severity of road accidents is an important and an active research area. Recently, most TSR approaches of machine learning and image processing have achieved advanced performance in traditional natural scenes. However, there exists...
As an artificial intelligent technique, artificial neural networks (ANNs) have been applied successfully in a wide range of fields due to its effective learning ability. In this paper, we conduct an empirical application on fragrance bottle form design due to its wide variety of appearances. For getting a better structure of the ANN model to develop the consumer-oriented expert system, we conduct...
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...
We present a novel method for training (evolving) fully convolutional neural networks (CNNs) for deformable object manipulation. Instead of using a weight update rule, we evolve an ensemble of compositional pattern generating networks (CPPNs) by means of a genetic algorithm (GA). These ensembles generate the convolutional kernels that comprise the CNN. This allows the GA to search for fit kernels...
We present an approach for unsupervised computation of local shape descriptors, which relies on the use of linear autoencoders for characterizing local regions of complex shapes. The proposed approach responds to the need for a robust scheme to index binary images using local descriptors, which arises when only few examples of the complete images are available for training, thus making inaccurate...
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...
In the paper we consider a new method based on the neural network for finding the location of small holes in the domain, in which the coupled linear and nonlinear boundary value problems are defined. The linear and nonlinear components are connected by the transmission conditions on the interface boundary. We use an artificial neural network, which calculates the locations of hole in the linear component...
The number of known and unknown plant species increases as time goes by. Research on plant species can be further advanced if there is a quick and accurate system that can identify plants and hasten the classification process. This system will not only help in accelerating plant classification, but will also allow people who are not morphological experts to conduct their own studies. LeaVes is an...
We describe for the first time how the Euler number of a 2-D binary image can be obtained by means of Artificial Neural Network (ANN). Calculating the Euler image number is treated as a pattern classification problem. To arrive at the specialized ANN architecture, we perform a partial results analysis provided by a known formulation to compute the Euler image number. We use this analysis for designing...
As a method to recover 3D shape under point light source and perspective projection, a method to recover the depth distribution has been proposed using optimization with both photometric and geometrical constraints which represents the relation between an interesting point and neighboring points under the assumption of Lambertian reflectance. This method assumes one light source at the same positions...
Red blood cell classification and counting plays a very important role in detecting diseases like iron deficiency anemia, vitamin B12 deficiency anemia etc. In this research we intend to develop a standalone application that can classify the red blood cells into four abnormal types namely elliptocytes, echinocytes, tear drop cells and macrocytes. We will also provide the total red blood cell count...
A general circuit model for the field-wire coupling effect of electrically small irregular wire structures of various geometries is proposed in this paper. The formulas for the circuit elements are presented in analytical form and the limitations are discussed in detail. Finally, the model is validated on three typical cases by comparing the coupling currents on the terminal load with the counterpart...
The monthly load curve forecasting problem is discussed, being tackled using artificial neural networks (ANN). Authors are proposing an enhanced algorithm that includes nonlinear optimization techniques, such as the conjugate gradient. Thus, a software-tool has been developed. Case study refers to a real distribution network operator from the Western part of Romanian Power System.
All around the world, poisonous scorpions are still considered as a public health issue. The scorpion's species can be determined by its physical characteristics. Different methods have been applied to differentiate among different insects, such as bugs, bees and moths. However, none have been applied to distinguish between different scorpion species. This paper presents a procedure to distinguish...
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