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Nonnegative matrix factorization (NMF) based hyperspectral unmixing aims at estimating pure spectral signatures and their fractional abundances at each pixel. During the past several years, manifold structures have been introduced as regularization constraints into NMF. However, most methods only consider the constraints on abundance matrix while ignoring the geometric relationship of endmembers....
In this paper we present a robust reconstruction framework on noisy and large point cloud data. Though Poisson reconstruction performs well in recovering the surface from noisy point cloud data, it's problematic to reconstruct underlying surface from large cloud data, especially on a general processor. An inaccurate estimation of point normal for noisy and large dataset would result in local distortion...
We develop a new non-parametric hierarchical information theoretic clustering algorithm based on implicit estimation of cluster densities using k-nearest neighbors (k-nn). Compared to a kernel-based procedure, our k-nn approach is very robust with respect to the parameter choices, with a key ability to detect clusters of vastly different scales. Of particular importance is the use of two different...
In this paper we propose a new method for appearance-based pose estimation, called Local Procrustes Regression (LPR). In LPR, rather than learning a map between all available training samples and pose space, as is common for appearance-based pose estimation algorithms, the pose of an unknown sample is recovered locally from a small subset of the training samples, by utilizing their inter-point distances...
This paper presents an alternative to the traditional impedance based fault location methods, using a simple technique of the learning approaches called k-Nearest Neighbors (k-NN), where besides the fault location distance, the multiple estimation problem is also addressed. This approach only uses the single end measurements of voltage and current available at the power substation. As principal advantage,...
As a non-contact-type device could sample part surface data with high speed and accuracy, it becomes the most popular instrument for capturing the surface data of a part. However, it creates a large amount of point data which must be reduced to decrease computational time and to lower the storage requirement. Aiming at the limitations of point cloud data reduction methods developed in the past, a...
In distribution systems, the determination of the load is relatively simple when measurements are available. Frequently, due to various causes such as metering and transmission equipment failures, data are missing for part or all of a day. In these cases, estimation a ldquocorrectedrdquo value must be made. The paper presents two methods (k-Nearest Neighbors, (kNNs) and Clustering methods) for treatment...
Software maintenance effort estimation is essential for the success of software maintenance process. In the past decades, many methods have been proposed for maintenance effort estimation. However, most existing estimation methods only produce point predictions. Due to the inherent uncertainties and complexities in the maintenance process, the accurate point estimates are often obtained with great...
Software cost estimation affects almost all activities of software project development such as: bidding, planning, and budgeting, thus it is very crucial to the success of software project management. In past decades, many methods have been proposed for cost estimation. Analogy based cost estimation (ABE) is among the most popular techniques due to its conceptual simplicity and empirical competitiveness...
In this paper, we present an automatic Motherese detection system for the study of parent-infant interaction analysis. Motherese is a speech register directed towards infants and it is characterized by higher pitch, slower tempo, and exaggerated intonation. The goal of this paper is to propose and evaluate different approaches for the detection of Motherese from home movies. We investigated the characterization...
Pattern recognition provides solution to many problems in real life such as in biometric system, personal identification of banks etc. It matches two point sets and consequently identify if they are identical. This is applicable in fingerprint recognition with minutiae as a representation, which has been widely used as an individual identification method. Fingerprint recognition is divided into two...
Mapping forest variables and associated characteristics is fundamental for forest planning and management. Considerable effort has been made in Northern Europe to develop techniques for wall-to-wall mapping of forest variables. Following that work, we describe the k-nearest neighbors (kNN) method for improving estimation and to produce wall-to-wall basal area, volume, and cover type maps, in the context...
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