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One-bit transform (1BT), followed by binary motion estimation, is an effective alternative for accelerating traditional 8-bit motion estimation (ME) in video coding. The underlining assumption in the design of 1BT methods is that natural videos contain noise. For screen content videos, however, the special characteristics (e.g. screen content is typically noise-free) can be exploited to further improve...
Activity recognition with triaxial accelerometer embedded in mobile phone is an important research topic in pervasive computing field. The research results can be widely used in many healthcare or data mining applications. Numerous classification algorithms have been applied into the activity recognition tasks. Among these algorithms, ELM (Extreme Learning Machine) shows its advantages in generalization...
Hyperspectral image classification is one of the most significant topics in remote sensing. A large number of methods have been proposed to improve the classification accuracy. However, the improvement often comes at the cost of higher complexity. In this work, we mainly focus on the Markov Random Fields related paradigm, which involves a demanding energy minimization procedure. Traditional methods...
Wireless sensor networks (WSNs) are widely used in variety fields, especially in the Web of Things. The sensor localization information is important for the capability of it. The centroid algorithm is a kind of no ranging location algorithm, which is widely used in the positioning in WSN. To improve the positioning accuracy, this paper puts forward an improved weighted centroid algorithm, then self-corrected...
With the wide application of web database, Web pages are continuously deepened. In order to use Deep Web resources effectively, the Deep Web data need to be integrated on a large scale, and data sources discover is the primary work of Deep Web resources integration. The Deep Web site found efficiently is the key of the Deep Web data Integration. This paper puts forward a kind of Deep Web entry automatic...
In medical image analysis, atlas-based segmentation has become a popular approach. Given a target image, how to select the atlases with the similar shape of anatomical structure to the input image is one of the most critical factors affecting the segmentation accuracy. In this paper, we propose a novel strategy by putting the images on a manifold to analyze the intrinsic similarity between the images...
This paper proposes a new strategy which combines the principle of golden and the quasi-Newton iterative method, when search peak and estimate the LFM signal's parameters with fractional Fourier transform. The new strategy set the step value in the golden section when search the LFM signal FRFT's peak, and then take advantage of the quasi-Newton iterative method to accurately estimate the LFM signal's...
Iris, as a biometric with the best performance in the stability, reliability and non-invasiveness, can obtain an even more high recognition rate than other biometrics, such as fingerprint, face and voice. However, it is difficult to extract iris features from an eye image. In this paper, we demonstrate a scheme for iris detection and extraction based on John Daugman's Integro-differential operator...
Location-based measurement equipments are widely used in practice. However, the traffic data they collected are restricted in small spatial scale. Recently, more and more trajectory-based equipments are introduced in field. Floating cars and cell phones are two promising products. Since large market penetration of cell phones, they have attracted more and more attention. The use of cell phone signals...
Current investment in crop monitoring consumes a large amount of financial cost, and how to reduce this cost has been a long-standing problem in agriculture. Traditional crop monitoring approaches are not cost-effective, because they rely on either heavy human labor or intensive computation with expensive instruments. In this paper, we explore the possibility of deploying networked sensor nodes for...
The paper presents three kinds of grey neural network combined model for short-term prediction of urban traffic parameters, which are parallel grey neural network, series grey neural network, and inlaid grey neural network. They are employed to forecast a real vehicle speed in Barbosa road of Macao with satisfied precision. The experiment shows that the above three kinds of mode are feasible and effective...
Analyzing notor imagery electrocardiogram (ECoG) signal is very challenging for it is hard to set up a classifier based on the labeled ECoG obtained in the first session and apply it to the unlabeled test data obtained in the second session. Here we propose a new approach to analyze ECoG trails in the case of session-to-session transfer exists. In our approach, firstly, dimension reduction is performed...
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