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Given very few images containing a common object of interest under severe variations in appearance, we detect the common object and provide a compact visual representation of that object, depicted by a binary sketch. Our algorithm is composed of two stages: (i) Detect a mutually common (yet non-trivial) ensemble of `self-similarity descriptors' shared by all the input images. (ii) Having found such...
Many different formal tools, e.g. statistic, fuzzy logic, neural networks, are used to study different bankruptcy related tasks. A qualitative modeling philosophy has been developed in an effort to produce a general and reasonably unified common sense approach to modeling of unique, complex and unsteady state systems. A qualitative description is information non intensive as it is based just on three...
We propose an efficient method, built on the popular Bag of Features approach, that obtains robust multiclass pixel-level object segmentation of an image in less than 500ms, with results comparable or better than most state of the art methods. We introduce the Integral Linear Classifier (ILC), that can readily obtain the classification score for any image sub-window with only 6 additions and 1 product...
The automatic detection of lung nodules attached to other pulmonary structures is a useful yet challenging task in lung CAD systems. In this paper, we propose a stratified statistical learning approach to recognize whether a candidate nodule detected in CT images connects to any of three other major lung anatomies, namely vessel, fissure and lung wall, or is solitary with background parenchyma. First,...
People social interaction analysis is a complex and interesting problem that can be faced from several points of view depending on the application context. In videosurveillance contexts many indicators of people habits and relations exist and, among these, people trajectories analysis can reveal many aspects of the way people behave in social environments. We propose a statistical framework for trajectories...
We present a general methodology that aims to learn multi-variate statistics of high dimensional images, in order to capture the inter-individual variability of imaging data from a limited number of training images. The statistical learning procedure is used for identifying abnormalities as deviations from the normal variation. In most practical applications, learning an accurate statistical model...
This paper presents a new approach to generate hypotheses about the presence of pedestrians in an infrared image. Information about maximally stable extremal regions is used to locate the warmest regions on the image, which are considered to be potential human heads. To capture the complete human body, these regions are scaled based on the range data of a lidar sensor. Closely related regions are...
Response surface designs investigating the effects of several factors have widely application and make the researcher or analyst to control the factors or model the effects of the input variables on the response of the process. Outliers among the measurements can almost be inevitable and will frequently have a highly confusing effect on response surface design, consequently leading to a wrong interpretation...
Neurological diseases can cause atrophy of the corpus callosum resulting in a change in its size and shape. The measurement and analysis of this change is one of the goals of clinical research. We perform statistical analysis of the shape of the corpus callosum extracted from MR brain scans of a group of multiple sclerosis patients undergoing a longitudinal (serial) study. In contrast to the classical...
Load curve analysis is an efficient instrument aimed at carrying through studies and planning, necessary for developing electric energy distribution networks and for reducing the electric energy internal consumption. The paper herein presents the analysis of the load curves for an industrial consumer fed from the network of 20 kV, 50 Hz. There are calculated the characteristic parameters for daily...
This paper deals with optimum design criteria for maximum torque density & minimum torque ripple of Flux Switching Motor (FSM) using response surface methodology (RSM) & finite element method (FEM). The focus of this paper is to find a design solution through the comparison of torque density and torque ripple according to rotor shape variations. And then, a central composite design (CCD) mixed...
The investment in fixed assets has shown a sustained and rapid growth in China. There is an urgent need for statistics department to establish a stable and efficient fixed asset investment Projects monitoring and management information system. On the basis of in-depth analyze on statistical business process, the details of system framework, database design, and the function modules are described....
Surface wave (SW) over-the-horizon (OTH) radars are not only widely used for ocean remote sensing, but they can also be exploited in integrated maritime surveillance systems. This paper represents the first part of the description of the statistical and spectral analysis performed on sea backscattered signals recorded by the oceanographic WEllen RAdar (WERA) system. Data were collected on May 13th...
A new voltage ramp dielectric breakdown (VRDB) methodology based on square root (SQRT) E model for dielectrics reliability evaluation was developed. We conducted VRDB and time dependent dielectric breakdown (TDDB) experiments on dielectrics in Cu/low-k interconnect for reliability assessment. The experimental results show very good correlation between VRDB and TDDB data underlying SQRT E model. The...
Vein Pattern is the vast network of blood vessels underneath a person's skin. Anatomically, the shape of vascular patterns in the back of the hand is unique to the individual even for identical twins and it remains stable over a long period. The properties of uniqueness, stability and strong immunity to forgery of the vein pattern make it a potentially good biometric trait. In this study, we present...
The practical methodologies of stable pattern classification using artificial intelligence as advisory tools are researched here according to studies in the flowering plant genera Lithops N. E. Br. (Aizoaceae). In this paper, the use of a neural network model with the adaptive resonance theory is a practical generation of groups as a classifier for botanical taxa. In order to provide comparisons for...
We introduce a novel method for the evaluation of statistical shape models (SSM) that allows for quantifying the model quality wrt. global and local shape properties. The construction of SSM requires the identification of corresponding landmarks across a set of training shapes. Establishing such correspondence is a delicate matter and demands for automatic methods in a 3D setting. Conversely, the...
As medical imaging datasets continue to grow, interest in effective ways to analyze the statistical properties and data variability within those datasets has surged. Accurate analysis of the morphological statistical properties of a group of images has proven to be extremely important in medical imaging. This paper introduces Relational Statistical Deformation Models, or RSDMs, as a generic modeling...
We present a study of the spatial variation of nuclear morphology of stromal and cancer-associated fibroblasts in the mouse mammary gland. The work is part of a framework being developed for the analysis of the tumor microenvironment in breast cancer. Recent research has uncovered the role of stromal cells in promoting tumor growth and progression. In specific, studies have indicated that stromal...
Similar characters existed in Chinese character affect much on enhancing the handwritten Chinese character recognition rate. An improved method is presented in this paper, which combines structural and statistical features for similar handwritten Chinese character recognition,. Four-corner code feature that based on stroke structure is used to get the similar character set. According to the different...
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