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A safe real-time imitation framework for humanoid robots to human beings action is proposed. Postures of an actor are divided into three categories: robust postures, normal postures and dangerous postures. To deal with the robust postures, direct mapping from skeleton data gathered by 3D cameras to each angle of robot joint motors is taken because the postures are robust enough for imitation in high...
Vehicle identification is one of the frequently studied problems in video surveillance. Commonly, identifying an unknown vehicle object requires a large amount of training instances. Unfortunately, in the large parking scenario, the cost may be prohibitively expensive because of the finitely waiting time from the car owners. In this paper, we show that it is possible to identify a registered vehicle...
It is well known that feed-forward neural networks can be learnt from symbolic data although the learnt networks usually have poor performance. This paper explores the ability of a recently popular feed-forward neural network, i.e., Extreme Learning Machine (ELM) for modeling symbolic data. An experimental study is conducted to compare C4.5 (a very popular algorithm of learning from symbolic data)...
From a perspective of feature extraction, we present a histogram-based sparsity descriptor (HSD) which is derived from the robust principal component analysis (RPCA) and histogram technique. Given a test image, sparse error images with respect to each class can be obtained by using RPCA decomposition. In order to extract the facial features in terms of intensity distribution, a sparseness measure...
Man-machine game is an important component in the field of artificial intelligence. Game tree search algorithms and chess situation evaluation functions are mostly applied in the traditional chess game system. When the game tree method is used, the response time will be extended as the depth of tree. This paper proposes to use the stochastic weight assignment neural network (SWAN), trained by Extreme...
Data quality plays an important role in modern intelligent information system and is crucial to any data analysis task. Many imperfection-handling techniques avoid overfitting or simply remove offending portions of the data. Data correction can help to retain and recover as much information as possible from the original data resources. In this paper, we proposed a novel technique based on polynomial...
Heart failure (HF), the terminal stage of all kinds of cardiovascular disease, has a high level of morbidity and mortality. But the heavy burden of curing and managing HF can be largely reduced by early detection of it. Motivated by this problem, we study methods to determine its risk factors based on extreme learning machine (ELM). Several state-of-the-art data mining algorithms are employed to estimate...
Data mining methods like clustering enable police to get a clearer picture of criminal identification and prediction. Clustering algorithms will help to extracts hidden patterns to identify groups and their similarities. In this paper, a modified k-mean algorithm is proposed. The data point has been allocated to its suitable class or cluster more remarkably. The Modified k-mean algorithm reduces the...
Chromatography has been widely used in discrimination and quality control for Chinese medicines (CMs). Nevertheless, regular analytical approaches are not applicable if training samples are small while features are large. Support vector machine (SVM) with recursive feature elimination algorithm (RFE-SVM) is presented in this study for discrimination of Pericarpium Citri Reticulatae through small chromatographic...
In this study, an eye-tracking system based on FPGA hardware and the center of gravity algorithm is proposed. It captures video via LUPA300 high-speed CMOS and obtains the motion of eye pupil and bright spot through the continuous video frames by using a FPGA implemented the center of gravity algorithm. To obtain a reliable tracking accuracy, a series of binarization and mathematical morphology operations...
Face detection is a challenging research area and crucial step of face detection system. Because of the factors of rotation, pose change, and complicated background, false faces also can be found in detection results. This paper puts forward a new approach based on the landmark localization to detect face image which includes various pose variation. Furthermore, the proposed histogram of sparse code-based...
In this paper, we suggest an accessible and effective approach to the urban road state estimation. The main technical contribution of the proposed method is a novel feature extraction on the basis of the multi-resolution, along with support vector machine for classification. Experimental tests have been carried out to validate our proposed approach which can estimate road state in the sample of a...
The problem of judging direction of the road is a tough problem in navigation system. This paper presents a image-based approach to address the direction problem in the road using Support Vector Machine(SVM) and Bayesian rules. Established localization or orientation algorithm is infeasible in the direction problem due to its time and space complexity. SVM is employed as an effective model for classification...
This paper proposes a novel fuzzy forecasting method for forecasting the TAIEX based on optimal intervals and a similarity measure between the subscripts of fuzzy sets, where two threshold values α and β and a weighting constant γ are used, α ∊ [0, 1], β ∊ [0, 1] and γ ∊ [0, 1]. First, we use particle swarm optimization (PSO) techniques to obtain optimal intervals in the universe of discourses (UODs)...
This paper presents a new personalized recommendation technology for e-commerce website, which combines clustering users' expectations and Item-Based Collaborative Filtering recommendation algorithm. Similar distance between two websites means similar expectations. Firstly we cluster the websites by calculating the distance between any two websites. Naturally, the expected distance matrix of websites...
In this paper, a validity index method VDOGK, a variation of the index method VDO, for estimating the optimal number of clusters in datasets with concave-/elongated-shaped clusters is presented. The new index uses Gustafson-Kessel FCM to partition the dataset so that geometric-shape-sensitivity problem of FCM can be reduced. It is based on both dispersion and overlap measures, where the dispersion...
This work develops a new density-based clustering scheme, TSS-DBSCAN, which uses DBSCAN and a new method of applying two-phase screening, to reduce the extent of the meaningless expansion of clustering to improve data clustering for numerous related applications. Experimental results demonstrate that the proposed new TSS-DBSCAN scheme has very high noise filtering rate and clustering accuracy (both...
This investigation presents a new metaheuristic algorithm called GR-2opt, that hybridizes the greedy algorithm and the 2-opt method to solve the traveling salesman problem (TSP). The developed method integrates an excellent strategy for interactively improving the candidate solution. To confirm the presented approach, various experiments are carried out to compare the proposed algorithm with numerous...
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