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With the exponential increase of the data scale, the problem of feature selection has been the focus in statistical pattern recognition. In this paper, a new modified forward deep floating searching algorithm (SDFFS) is proposed to select a feature subset of d features from the original candidate-set of D features (d < D), which is an improvement of the state of the art SFFS algorithm. The SDFFS...
Localization is a way to find the blind node's position through some anchor nodes whose positions are known before, which is the essential issue of wireless sensor networks (WSN). Among all the localization algorithms, maximum likelihood localization (ML) algorithm based on received signal strength (RSS) is more accurate than most of other algorithms. However, ML algorithm needs to compute conjugate...
Because MapReduce supports efficient parallel data processing, MapReduce-based query processing algorithms have been widely studied. Among various query types, k-nearest neighbor join, which aims to produce the k nearest neighbors of each point of a dataset from another dataset, has been considered most important in data analysis. Existing k-NN join query processing algorithms on MapReduce suffer...
Land-use change is one of main factors of coastal erosion. This research aimed to integrate techniques of remote sensing and geographic information system to investigate the relationship between land-use changes and coastal erosion in Phuket Island, Thailand, using multi-sensors and temporal imageries acquired during 2003–2011. Eight land-use classes including built-up, forest, mangrove forest, agriculture,...
Non-randomness within canopies and woody component are two factors limiting the accuracy of indirect leaf area index (LAI) measurement. Here we combine the path length distribution model and Multispectral Canopy Imager (MCI) together for the first time to improve the accuracy. The results show that non-randomness within canopies underestimates 17.1%-28.2% LAI, while woody component overestimates 14...
There are two great challenges for classification of hyperspectral images (HSIs): lack in prior knowledge and serious internal-class variability. To address the issues, we propose a novel semisupervised method based on affinity scoring (AS). It can harness the fuzzy state of the contributions of spectral and spatial features to classification. The method consists of three major steps: over-segmentation,...
Aim at the ill-posedness of vegetation biophysical variables inversion problems, the paper presents a multi-scale, multistage (MSMS) inversion approach based on field data, multi-resolution remotely sensed observations and spatial knowledge for estimating crop leaf area index (LAI). The proposed MSMS inversion method takes advantage of multiple stages inversion strategy and prior information. Firstly,...
In the past SAR data has been proven as a great source for land cover characterization. For classification purpose many individual methods has been used, but single method are likely to undergo high variance or biasness depending on the base used for classification. Hence, in this paper random forest classification technique has been used for SAR data classification into different land cover classes...
This study addresses the detection of the land degradation in the arid and semi-arid areas using remote sensing techniques. Using free data like Landsat and Shuttle Radar Topography Mission (SRTM) DEM, we mapped land degradation and its factors in Western Australia. By combining vegetation index estimated from Landsat data and geographic information calculated from SRTM DEM, the land situation was...
The precision of visual matching and the trade-off between accuracy and time efficiency have long been bottlenecks of image search systems. This work addresses the two problem simultaneously by introducing the coupled Multi-Index (cMI) structure. First, by combining SIFT and color features on the indexing-level, the discriminative power of visual words is greatly enhanced. Second, by reducing the...
Accurate estimation of dynamic states is important for monitoring and controlling transient stability. This paper proposes an adaptive interpolation approach to improve the performance of the Extended Kalman Filter (EKF) for estimating dynamic states of a synchronous machine. This approach consists of two major steps. First, the non-linearity of state transition function and measurement function is...
In this paper, three individual indices, as well as a new comprehensive index, are introduced to evaluate prediction intervals. Then, two practical methods, namely, Interval Extension Method and Optimal Scalar Method are proposed to build the prediction intervals based on an ensemble of Extreme Learning Machines. Case studies on hour-ahead load interval forecasting with respect to Chicago Metro Area...
With the rapid development in science and technology, data acquisition, storage and mining technology are widely applied to various fields. All aspects of people's lives are recorded as data. Through the analyzing and arranging of data, people can get a lot of valuable information. In this paper, support vector machine (SVM), least squares support vector machine (LSSVM) and partial least squares (PLS)...
Software evaluation of elementary functions usually requires three steps: a range reduction, a polynomial evaluation, and a reconstruction step. These evaluation schemes are designed to give the best performance for a given accuracy, which requires a fine control of errors. One of the main issues is to minimize the number of sources of error and/or their influence on the final result. The work presented...
Context aware systems like smart homes and offices will benefit from determining human-object and human-human interactions. In this paper, we explore interaction detection methods using only wearable Inertial Measurement Units (IMUs). The interactions we explore involve two actors — the primary person and a secondary object or person. We explore how several commonly used time domain signal processing...
Active triangulation has been successfully applied in numerous applications such as distance measurement, profile inspections and pose estimation in robotics. Its accuracy depends on many factors with locating laser centroid being one of them. The error generated in locating the laser centroid within the image is propagated to the system output with consequences in decreasing performance. In this...
For music identification, conventional bag of audio words model methods generally compute a histogram for a piece of music, which ignores the temporal characteristic of music and has a negative influence on the accuracy. In addition, they are usually based on DFT spectrogram, which cannot represent music as well as Constant Q (CQ) spectrogram. To address the above problems, we propose a two-layer...
In this paper we present an innovative method for counting people from zenithal mounted cameras. The proposed method is designed to be computationally efficient and able to provide accurate counting under different realistic conditions. The method can operate with traditional surveillance cameras or with depth imaging sensors. The validation has been carried out on a significant dataset of images...
As the number of cooking recipes posted on the Web increases, it becomes difficult to find a cooking recipe that a user needs. Moreover, even if it can be done, it is still difficult for users to arrange the cooking recipe, for example, by replacing ingredients with different ones. To deal with such problems, we propose a framework for typicality analysis of the combination of ingredients. The framework...
In this paper, a clothes segmentation method for fashion parsing is described. This method does not rely in a previous pose estimation but people segmentation. Therefore, novel and classic segmentation techniques have been considered and improved in order to achieve accurate people segmentation. Unlike other methods described in the literature, the output is the bounding box and the predominant color...
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