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Classification of vehicle logo is an important step towards the vehicle recognition that is required in many applications in intelligent transportation systems and automatic surveillance. A fast and reliable vehicle logo classification approach is proposed by first accurate logo detection, followed by an improved local-mean based classification algorithm. The recently published integrative logo detection...
This paper presents a novel Matching Propagation Framework for addressing the problem of finding better matching pairs between each two images, which is one of the most fundamental tasks in computer vision and pattern recognition. We first select initial seed points by original matching method like SIFT, and then use T-CM to explore more seed points. Finally, a triangle constraint based quasi-dense...
Virtual screening based on protein-ligand docking is widely applied at the early stage of drug discovery. Scoring functions from a diverse set of existing protein-ligand docking tools, however, often poorly distinguish bioactive compounds from inactive ones. As a result, considerable effort has been devoted to the combination of multiple scoring functions for more reliable evaluation. State-of-the-art...
The problem of plant seed identification is important for agricultural sector, such as maintaining seed quality and to prevent the spreading of weed species. Seed identification is currently performed by a human seed analyst; human must often search through many seed images before finding the desired seed. This process of manual identification is slow and posses a degree of subjectivity which is hard...
Cellular Data Network measurement and analysis has long been used to characterize Cellular Data Network usage and user behaviors, but with the rapid growing of all kinds of smart terminals and the varied applications on them, the amount of Cellular Data Network data has been growing exponentially. With respect to this challenge, a new management system for the data storage and query has been emerging...
In the communications field, many methods have been introduced in order to improve the quality of signal reception. This is because various parameters can limit the quality of signal reception such as multipath fading and interference that results the signal with low signal-to-noise ratio (SNR) or no signal reception. This paper presents a multi-receiver system to improve signal reception and classification...
This paper puts forwards a novel adaptive underfrequency load shedding method preventing system collapse under severe active-power deficits. The method has advantages over existing self-adaptive schemes in that it can accurately estimate the actual active-power deficit without knowing the system equivalent inertia, system boundary or constructing a control center. The method only measures the local...
The procedure of tolerance design is suggested for distribution laws given by statistical series. The scattering region is formed as box having smoothing vertices. The approximation of boundary section of statistical series is used by normallike distribution law. This method can be used for modal distribution law.
This work addresses to problems in design and testing of the computer systems and their components, which are considered in content of natural development of the resources for solving these challenges. The resources are examined as target and natural. The target resources contain the models, methods and means. The natural resources are considered like their particularities. Development of the resources...
In this work the Network Localization Problem with noisy measurements and mobility is considered. In particular, we first focus on the discovery of the localizable subnetwork by introducing an iterative approach to detect and merge small localizable components. Furthermore, we propose a novel check to mitigate the risk of flips ambiguities in order to enlarge the aforementioned subnetwork. Successively,...
In the last few years there has been growing interest in the use of functional Magnetic Resonance Imaging (fMRI) for brain mapping. To decode brain patterns in fMRI data, we need reliable and accurate classifiers. Towards this goal, we compared performance of eleven popular pattern recognition methods. Before performing pattern recognition, applying the dimensionality reduction methods can improve...
In order to obtain the down hole information involving ESP equipment to guide oil production, a down hole multi-parameter monitoring system based on current loop data transmission method was developed. Compared with other transmission methods in harsh environment, the current loop data transmission method possesses obvious advantage in reliability and accuracy. By ESP motor's three-phase winding and...
Latent fingerprint images are typically obtained under non-ideal acquisition conditions, resulting in incomplete or distorted impression of a finger, and ridge structure corrupted by background noise. This necessitates involving latent experts in latent fingerprint examination, including assessing the value of a latent print as forensic evidence. However, it is now generally agreed that human factors...
It is inevitable to capture a portion of iris images with motion blur during iris recognition. The texture details on iris patterns are lost in motion blurred images so it may cause recognition performance degradation. This paper presents a first systematic study on the issue of motion blurred iris image recognition. Firstly, the reason of generating motion blurred iris images is analyzed. Secondly,...
Due to the global economic crises, demand forecasting is becoming a critical issue to assure high level customers' service and strategies effectiveness. This is even more important for the fashion industry were forecasts are used both for yearly demand estimations and for real-time forecasts. Yearly estimations are usually important because it is difficult in terms of production rate to face demand...
One of the principles of Smart Grids is to have a communication network that will integrate equipment allowing the monitoring and operation to be performed in real time in order to improve the quality indicators. However, this migration to an automated and monitored environment will demand many resources that will be used to perform the migration gradually. Therefore, this work proposes a methodology...
The recognition of handwritten characters is an almost solved problem thanks to efficient machine learning techniques. However, the evaluation and the choice of thresholds to meet a certain level of performance remains a challenge. In this paper, we compare different rejection techniques to determine if a character has been successfully detected or not. Whereas the evaluation of binary classifiers...
In online social networks (OSNs), it is an open challenge to select proper recommenders for predicting the trustworthiness of a target. In real life, people who are close and influential to us can usually make more proper and acceptable recommendations. Based on this observation, we present the idea of recommendation-aware trust evaluation (RATE). We further model the recommender selection problem...
Multi-camera multi-object tracking problem can be regarded as a multi-player game by adopting a game theoretical approach. In embedded vision sensor networks, energy, processing power and bandwidth are limited, and should be efficiently used. In this paper, in addition to dynamic grouping of the camera nodes, we focus on the (re)assignment of object tracking tasks by simultaneously considering energy...
Different etiquette of software could trigger different attitudes and behaviors of users. This paper conducted a series of word-learning studies in which users either received polite feedback offering compliments and encouragements, or impolite feedback belittling users. Through the analysis on the results of e-learning experiment and post-test questionnaires, it was found that the polite feedback...
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