Search results for "Intelligence"

Divisive normalization image quality metric revisited.

2010

Structural similarity metrics and information-theory-based metrics have been proposed as completely different alternatives to the traditional metrics based on error visibility and human vision models. Three basic criticisms were raised against the traditional error visibility approach: (1) it is based on near-threshold performance, (2) its geometric meaning may be limited, and (3) stationary pooling strategies may not be statistically justified. These criticisms and the good performance of structural and information-theory-based metrics have popularized the idea of their superiority over the error visibility approach. In this work we experimentally or analytically show that the above critic…

Three-dimensional Fuzzy Kernel Regression framework for registration of medical volume data

2013

Abstract In this work a general framework for non-rigid 3D medical image registration is presented. It relies on two pattern recognition techniques: kernel regression and fuzzy c-means clustering. The paper provides theoretic explanation, details the framework, and illustrates its application to implement three registration algorithms for CT/MR volumes as well as single 2D slices. The first two algorithms are landmark-based approaches, while the third one is an area-based technique. The last approach is based on iterative hierarchical volume subdivision, and maximization of mutual information. Moreover, a high performance Nvidia CUDA based implementation of the algorithm is presented. The f…

Functional statistics based method for the evaluation of the registration of sequences of 3D perfusion MR images

2011

Accurate registration of medical images is a necessary task for several important diagnosis techniques. Nevertheless, it is a difficult challenge due to movement of the patient, deformations, noise in the signal, etc. Besides, evaluation of the quality of the performed registration is also troublesome, specially when no golden pattern (true result) is available and/or when the signal values may have changed between successive images/volumes to be registered.

Applying Wavelet Packet Decomposition and One-Class Support Vector Machine on Vehicle Acceleration Traces for Road Anomaly Detection

2013

Road condition monitoring through real-time intelligent systems has become more and more significant due to heavy road transportation. Road conditions can be roughly divided into normal and anomaly segments. The number of former should be much larger than the latter for a useable road. Based on the nature of road condition monitoring, anomaly detection is applied, especially for pothole detection in this study, using accelerometer data of a riding car. Accelerometer data were first labeled and segmented, after which features were extracted by wavelet packet decomposition. A classification model was built using one-class support vector machine. For the classifier, the data of some normal seg…

Review of machine to machine communication in smart grid

2016

Machine to machine communication (M2M) is a communication architecture that enables heterogeneous devices to interact with each other without human intervention. Smart Grid (SG) is one of the many applications areas in the M2M communication. Smart Grid demands advanced communication infrastructure for two-way communications between devices deployed at various locations in energy generation, transmission, distribution and consumption. The billions of electronic devices connected to the Smart Grid pose a big challenge to grid communication. Therefore, a feasible solution to efficient M2M has to overcome challenges of energy efficiency of connected devices, interoperability, coverage area, int…

A kernel support vector machine based technique for Crohn’s disease classification in human patients

2017

In this paper a new technique for classification of patients affected by Crohn’s disease (CD) is proposed. The proposed technique is based on a Kernel Support Vector Machine (KSVM) and it adopts a Stratified K-Fold Cross-Validation strategy to enhance the KSVM classifier reliability. Traditional manual classification methods require radiological expertise and they usually are very time-consuming. Accordingly to three expert radiologists, a dataset composed of 300 patients has been selected for KSVM training and validation. Each patient was codified by 22 extracted qualitative features and classified as Positive or Negative as the related histological specimen result showed the CD. The eff…

2021

Strength training exercises are essential for rehabilitation, improving our health as well as in sports. For optimal and safe training, educators and trainers in the industry should comprehend exercise form or technique. Currently, there is a lack of tools measuring in-depth skills of strength training experts. In this study, we investigate how data mining methods can be used to identify novel and useful skill patterns from a binary multiple choice questionnaire test designed to measure the knowledge level of strength training experts. A skill test assessing exercise technique expertise and comprehension was answered by 507 fitness professionals with varying backgrounds. A triangulated appr…

Geometric Algebra Rotors for Sub-symbolic Coding of Natural Language Sentences

2007

A sub-symbolic encoding methodology for natural language sentences is presented. The procedure is based on the creation of an LSA-inspired semantic space and associates rotation operators derived from Geometric Algebra to word bigrams of the sentence. The operators are subsequently applied to an orthonormal standard basis of the created semantic space according to the order in which words appear in the sentence. The final rotated basis is then coded as a vector and its orthogonal part constitutes the sub-symbolic coding of the sentence. Preliminary experimental results for a classification task, compared with the traditional LSA methodology, show the effectiveness of the approach.

Sub-symbolic Encoding of Words

2003

A new methodology for sub-symbolic semantic encoding of words is presented. The methodology uses the WordNet lexical database and an ad hoc modified Sammon algorithm to associate a vector to each word in a semantic n-space. All words have been grouped according to the WordNet lexicographers’ files classification criteria: these groups have been called lexical sets. The word vector is composed by two parts: the first one, takes into account the belonging of the word to one of these lexical sets; the second one is related to the meaning of the word and it is responsible for distinguishing the word among the other ones of the same lexical set. The application of the proposed technique over all…

Line based motion estimation and reconstruction of piece-wise planar scenes

2011

We present an algorithm for reconstruction of piece-wise planar scenes from only two views and based on minimum line correspondences. We first recover camera rotation by matching vanishing points based on the methods already exist in the literature and then recover the camera translation by searching among a family of hypothesized planes passing through one line. Unlike algorithms based on line segments, the presented algorithm does not require an overlap between two line segments or more that one line correspondence across more than two views to recover the translation and achieves the goal by exploiting photometric constraints of the surface around the line. Experimental results on real i…