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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...
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...
Induction motors fail due to many reasons, and many are rewound two or more times during their lifetimes. It is generally assumed that a rewound motor is not as efficient as the original motor. Precise estimation of efficiency of a refurbished motor or any existing motor is crucial in industries for energy savings, auditing, and management. Full-load and partial-load efficiency can be measured by...
In this paper, an epileptic seizure event detection algorithm utilizing five features namely singular values, total average power, delta band average power, variance and mean, is proposed. Using CHB-MIT Scalp EEG Database, the calculations of the features are performed over a sliding window of one second. The algorithm was evaluated in terms of accuracy, sensitivity, specificity and failure rate....
Extremely large graphs, such as those representing the Web or online social networks, require prohibitively large computational resources for an analysis of any of their complex properties. In this paper, we investigate an algorithmic approach to overcoming this difficulty by inferring key properties of the full graph using a strategic sample of small subgraphs of the graph. We focus, in particular,...
A recommendation system learns a user's interests from her historical purchasing or watching behavior, which is disclosed to the recommendation system inevitably. Such a disclosure raises a serious concern in the public for the leak of users' privacy. For instance, a person who watches a lot of videos which are more preferred by women than men can be inferred as female. Recently, as a response to...
Data stored in educational database is increasing day by day. Data mining algorithms can be used to find hidden patterns from the student's database. These patterns can be used to find academic performance of students. The main aim of this study was to determine factors that influence the student's performance. This paper proposes Generalized Sequential Pattern mining algorithm for finding frequent...
Segmentation of the foreground objects is the primary step in many video analysis applications. The accuracy of the segmentation is dependent on an accurate background image that is used for background subtraction. The Teknomo-Fernandez (TF) algorithm is an efficient algorithm that quickly generates a good background image. A previous study showed the extendibility of the TF algorithm to higher number...
This paper proposes a kind of improved DV-Hop algorithm to solve the problem of low positioning accuracy in traditional DV-Hop algorithm. This method uses wavelet neural network to estimate the per-hop distance of the anchor nodes. In order to improve the positioning performance, the distance of per-hop is applied in the wireless sensor network. Simulation results show that, the localization error...
Arc detection is difficulty for the processing, assembly and testing of industrial production because of limitations of the detection method, algorithm and the instrument. The least-squares algorithm usually is used to fit data in circle detection. The application of the conventional least-squares algorithm is limited, its roundness error is bigger, and precision is lower. For detecting arc with data...
Background subtraction is widely used in battery-operated surveillance system. In the system, memory requirement and computational complexity are important issues due to a constraint of the hardware resource. We propose memory-efficient and low computational complexity background subtraction algorithm based on multi-background registration (MBR) technique algorithm.
The Pedestrian detection using Histograms of Oriented Gradients (HOG) is the most popular method to detect a human from a picture. However, it, calculates the HOG description, will cost too much time and can't meet the real-time request for detecting pedestrian from the video surveillance system. In this paper we present a novel algorithm for detecting a human from a video. Firstly, The improved approach...
Centroid Algorithm Localization is to fix position using the wireless sensor connections, which has larger error. To increase the localization accuracy, based on the fact that the centroid algorithm is comparative stable under the changing environment, and the conveniences of RSSI, a revised and improved centroid algorithm based on RSSI is proposed in this paper. Combined with the advantages of the...
The amount of resources needed to provision Virtual Machines (VM) in a cloud computing systems to support virtual HPC clusters can be predicted from the analysis of historic use data. In previous work, Hacker et al. found that cluster analysis is a useful tool to understand the underlying spatio-temporal dependencies present in system fault and use logs. However, the cluster analysis used for reducing...
Sequence-based localization is a novel RF localization technique. The algorithm is achieved by constituting RSSI-based constraint tables and comparing data between two tables. But, the definitions of the constraint relation and the centroid in the algorithm are imperfect. In this paper, we present a new sequence localization method that involves with correlation metric and centroid. First, we use...
Data process in Cloud or IoT (Internet of Things) sometimes implies continuous real-time queries as data streams. In order to acquire extreme value of data stream over time-based sliding window, traditional approaches computed the exact solution through vast space especially under ultra circumstances like high-rate or high-concurrency. In this paper, we design space-bounded synopsis data structure...
Building a photorealistic, 3D model of an object or a complete scene from image-based methods is a fundamental problem in computer vision, and has many applications in robotic perception, navigation, exploration and mapping. In this paper, we extend current state-of-the-art in the computation of depth maps by presenting an accurate and computationally efficient iterative hierarchical algorithm for...
In this paper, we propose a novel method to determine whether a scanned text document is right side up or upside down. The text documents discussed here are limited to English, Chinese and Japanese where we find that the punctuation marks located on the bottom of the text line have a much more frequent occurrence than those on the top. Thus, by calculating the number of punctuation marks on the bottom...
Image segmentation is an important research area in computer vision and many image segmentation methods have been proposed, therefore it is necessary to be able to evaluate the performance of image segmentation algorithms objectively. For natural images, usually we use interactive image segmentation to provide a means of accurately extracting semantic objects from an image efficiently. In interactive...
Localization is a fundamental issue which is studied for many wireless networks applications like robotic networks. However, the existing range-free indoor localization algorithms haven't provided sufficient accuracy. In this paper, we propose a Selective 3- Anchor DV-hop algorithm with the following idea: the normal node first selects any three anchors to form a 3-anchor group, then it calculates...
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