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Nowadays, with the development of navigation and location, many kinds of outdoor locating methods are surveyed and used, such as Global Position System (GPS) and LTE fingerprint-based positioning system. However, as the most compelling focus, the localization accuracies of these systems are limited by the location systems themselves. Therefore, in order to improve the localization accuracy, we should...
Subspace clustering is one of the active research problem associated with high-dimensional data. Here some of the standard techniques are reviewed to investigate existing methodologies. Although, there have been various forms of research techniques evolved recently, they do not completely mitigate the problems pertaining to noise sustainability and optimization of clustering accuracy. Hence, a novel...
In order to reduce the false matching rate and matching time, an improved algorithm based on RANSAC-SIFT was proposed. The feature points were extracted by SIFT algorithm firstly. Then most of the mismatching points were eliminated according to the constraints that matching distances tend to be consistent. Finally the remaining points were regarded as pre matching points for achieve fine matching...
The feature matching and tracking of binocular vision inter-frame images have been divided into three parts in this paper. Before image feature extraction, an image binarization segmentation method based on HSV color space is used to extract the target in order to reduce the searching range of feature points and improve the matching efficiency. About feature matching, a modified ORB method combining...
Iris recognition is a biometric authentication system proving vital for ensuring security and has been employed as an important case to test the algorithms developed in pattern recognition. The unique circular shape of the iris and its time invariance makes it a versatile technique that has an accuracy that can be mathematically proven. Here in this work we propose a new segmentation technique and...
This paper describes an algorithm that parallelizes support vector machines. The data is split into subsets and optimized separately with multiple SVMs, instead of analyzing the whole training set in one optimization step. The partial results are combined and filtered in a cascade of SVMs. The process terminates when the global optimum is reached. The Cascade SVM is spread over multiple processors...
Sentiment Analysis is the process of figuring out the emotions from a piece of writing that whether it is positive, negative or neutral and is used to tell the speaker's attitude. The trend, today, is to consider the opinions of a variety of individuals around the globe before purchasing an item using micro-blogging data. Customers tend to go over a lot of reviews about a particular item before buying...
The concept of indoor location positioning has been around for decades now. Despite the existence of many algorithms that can achieve location positioning with remarkable performance in terms of accuracy, implementation of such algorithms has not been done on a large scale. There is a trade-off between the positioning accuracy and the complexity of the algorithm. This paper introduces and explains...
In software projects, there is a data repository which contains the bug reports. These bugs are required to carefully analyse and resolve the problem. Handling these bugs humanly is extremely time consuming process, and it can result the deleying in addressing some important bugs resolutions. To overcome this problem, researchers have introduced many techniques. One of the commonly used algorithm...
Cluster Analysis methods are very important, popular data summarization techniques applied in diverse environments. These techniques retrieve the hidden patterns in large datasets in the form of characterized patterns which can be interpreted further in different contexts. Widespread use of medical information systems and explosive growth of medical databases require traditional manual data analysis...
A deoxyribonucleic acid (DNA) microarray is a powerful tool that is widely used in genetics to monitor the expression levels of thousands of genes in parallel. Gridding, segmentation and intensity extraction is the process of gene expression. In the process of gene expression, gridding process information leading to dig their own DNA and provide coordinates for each point. Gridding can be implemented...
Interpolation is among of the most popular approach used in approximating the values in logarithmic number system (LNS) arithmetic design. This method that often combines with lookup tables (LUTs) manages to produce efficient LNS design in area, latency and accuracy. Current research proves that the combination of interpolators with co-transformation in LNS subtraction had shown extreme improvements...
In Electronic Travel Aids for the blind, accurately tracking a planned path is the foundation and premise of security guiding. To satisfy the requirement of accuracy and adaptability, a continuous closed-loop control method based on intelligent adaptive PID algorithm is proposed. The dynamic model of the walking guidance system is established, and the control law and the initial parameters of intelligent...
We are living in the 21st century in which technological advances have greatly improved the quality of human lives. However nature keeps presenting its challenges in the form of tsunamis, floods, wild fires, hurricanes, volcanoes, etc. Excellent evacuation route planning is of paramount importance to reduce loss of lives during such disasters. The parameters of finite time lined capacity of evacuation...
3D point Geometric alignment is a challenging task encountered in many scientific applications related to different fields such as robotics and computer vision. For this reason, the well-known 3D registration problem has been extensively studied, and a lot of efficient 3D registration algorithms (RA) exist. Even though many surveys in the literature addressed RA's, none to our knowledge is especially...
A fuzzy confusion matrix based cursive handwritten text categorization has been implemented. Printed text is obtained from handwritten text through Modified Optimal Clustering Algorithm (MOCA). Optimal Clustering Algorithm (OCA) groups texts into different subject categories. Learning is conducted to extract the attributes along with corresponding weights for each subjects. Fuzzy confusion matrix...
Task Scheduling is one of the major challenges in any system, whether, parallel system, distributed system, cloud computing, where we execute more than one task at a time. In a distributed system one of issue is task scheduling, based on trusting the accuracy of the information about the resource availability. In a commercial multi-cloud environment, usually any individual providers are focused towards...
FCM is sensitive to initialization and tends to result in local minimum in iterations. This paper studies the crossover and mutation probability of genetic algorithm and presents a new crossover and mutation probability. The proposed clustering scheme based on genetic algorithm and fuzzy c-means takes full advantage of the global optimization of genetic algorithm and the local search ability of FCM...
Extensive research has been conducted in an effort to evaluate methods and techniques for image segmentation. However, while most literature has focused on evaluating automatic and semi-automatic algorithms, works evaluating interactive segmentation algorithms are less numerous. Note that interactive segmentation can improve results by adding prior knowledge from users into the process. Although this...
Urban expansion monitoring and organization can be performed through space-based observation thanks to the revisit time and level of details guaranteed by satellite remote sensing. In particular, the Landsat mission products are the most used thanks to the long time coverage and open access policy. This paper proposed a hybrid method — combination of pixel- and object-based analysis — in order to...
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