Search results for "Intelligence"
showing 10 items of 6959 documents
Evaluation of Record Linkage Methods for Iterative Insertions
2009
Summary Objectives: There have been many developments and applications of mathematical methods in the context of record linkage as one area of interdisciplinary research efforts. However, comparative evaluations of record linkage methods are still underrepresented. In this paper improvements of the Fellegi-Sunter model are compared with other elaborated classification methods in order to direct further research endeavors to the most promising methodologies. Methods: The task of linking records can be viewed as a special form of object identification. We consider several non-stochastic methods and procedures for the record linkage task in addition to the Fellegi-Sunter model and perform an e…
Learning to Navigate in the Gaussian Mixture Surface
2021
In the last years, deep learning models have achieved remarkable generalization capability on computer vision tasks, obtaining excellent results in fine-grained classification problems. Sophisticated approaches based-on discriminative feature learning via patches have been proposed in the literature, boosting the model performances and achieving the state-of-the-art over well-known datasets. Cross-Entropy (CE) loss function is commonly used to enhance the discriminative power of the deep learned features, encouraging the separability between the classes. However, observing the activation map generated by these models in the hidden layer, we realize that many image regions with low discrimin…
Bagging and Boosting with Dynamic Integration of Classifiers
2000
One approach in classification tasks is to use machine learning techniques to derive classifiers using learning instances. The co-operation of several base classifiers as a decision committee has succeeded to reduce classification error. The main current decision committee learning approaches boosting and bagging use resampling with the training set and they can be used with different machine learning techniques which derive base classifiers. Boosting uses a kind of weighted voting and bagging uses equal weight voting as a combining method. Both do not take into account the local aspects that the base classifiers may have inside the problem space. We have proposed a dynamic integration tech…
Real-time flaw detection on a complex object: comparison of results using classification with a support vector machine, boosting, and hyperrectangle-…
2006
We present a classification work performed on industrial parts using artificial vision, a support vector machine (SVM), boost- ing, and a combination of classifiers. The object to be controlled is a coated heater used in television sets. Our project consists of detect- ing anomalies under manufacturer production, as well as in classi- fying the anomalies among 20 listed categories. Manufacturer speci- fications require a minimum of ten inspections per second without a decrease in the quality of the produced parts. This problem is ad- dressed by using a classification system relying on real-time ma- chine vision. To fulfill both real-time and quality constraints, three classification algorit…
Real Time Robust Embedded Face Detection Using High Level Description
2011
Face detection is a fundamental prerequisite step in the process of face recognition. It consists of automatically finding all the faces in an image despite the considerable variations of lighting, background, appearance of people, position/orientation of faces, and their sizes. This type of object detection has the distinction of having a very large intra-class, making it a particularly difficult problem to solve, especially when one wishes to achieve real time processing. A human being has a great ability to analyze images. He can extract the information about it and focus only on areas of interest (the phenomenon of attention). Thereafter he can detect faces in an extremely reliable way.…
Managing Human Factors to Reduce Organisational Risk in Industry
2018
[EN] Human factors are intrinsically involved at virtually any level of most industrial/business activities, and may be responsible for several accidents and incidents, if not correctly identified and managed. Focusing on the significance of human behaviour in industry, this article proposes a multi-criteria decision-making (MCDM)-based approach to support organizational risk assessment in industrial environments. The decision-making trial and evaluation laboratory (DEMATEL) method is proposed as a mathematical framework to evaluate mutual relationships within a set of human factors involved in industrial processes, with the aim of highlighting priorities of intervention. A case study relat…
Target point calculation in the computerized tomography. Comparison of different stereotactic methods
1995
The adaptation of computerized tomography for stereotactic operations requires the transformation of the coordinates of the target point from the CT image space into the stereotactic frame space. Two basic solutions for this transformation are realized in the most of the contemporary stereotactical systems. The indirect geometric method adjusts the frame coordinate system mechanically and identifies its origin in the CT image. There are 6 degrees of freedom: 3 of rotation and 3 of translation which have to be taken into consideration. The second method is a based on direct algebraic coordinate transformation and is independent of the explicite knowledge of the relationship between the image…
Functional connectivity inference from fMRI data using multivariate information measures
2022
Abstract Shannon’s entropy or an extension of Shannon’s entropy can be used to quantify information transmission between or among variables. Mutual information is the pair-wise information that captures nonlinear relationships between variables. It is more robust than linear correlation methods. Beyond mutual information, two generalizations are defined for multivariate distributions: interaction information or co-information and total correlation or multi-mutual information. In comparison to mutual information, interaction information and total correlation are underutilized and poorly studied in applied neuroscience research. Quantifying information flow between brain regions is not explic…
On the Neurocognitive Co‐Evolution of Tool Behavior and Language: Insights from the Massive Redeployment Framework
2021
Understanding the link between brain evolution and the evolution of distinctive features of modern human cognition is a fundamental challenge. A still unresolved question concerns the co-evolution of tool behavior (i.e., tool use or tool making) and language. The shared neurocognitive processes hypothesis suggests that the emergence of the combinatorial component of language skills within the frontal lobe/Broca's area made possible the complexification of tool-making skills. The importance of the frontal lobe/Broca's area in tool behavior is somewhat surprising with regard to the literature on neuropsychology and cognitive neuroscience, which has instead stressed the critical role of the le…
Contributed discussion on article by Pratola [Comment on "M.T. Pratola, Efficient metropolis-hastings proposal mechanisms for Bayesian regression tre…
2016
Contains fulltext : 161650.pdf (Publisher’s version ) (Open Access) The author should be commended for his outstanding contribution to the literature on Bayesian regression tree models. The author introduces three innovative sampling approaches which allow for efficient traversal of the model space. In this response, we add a fourth alternative. 3 p.