Search results for "Artificial"
showing 10 items of 7394 documents
A distributed visualization system for crowd simulations1
2011
The visualization system of large-scale crowd simulations should scale up with both the number of visuals views of the virtual world and the number of agents displayed in each visual. Otherwise, we could have large scale crowd simulations where only a small percentage of the population is displayed. Several approaches have been proposed in order to efficiently render crowds of animated characters. However, these approaches either render crowds animated with simple behaviors or they can only support a few hundreds of user-driven entities. In this paper, we propose a distributed visualization system for large crowds of autonomous agents that allows the visualization of crowds animated with co…
Expert system for predicting unstable angina based on Bayesian networks
2013
The use of computer-based clinical decision support (CDS) tools is growing significantly in recent years. These tools help reduce waiting lists, minimise patient risks and, at the same time, optimise the cost health resources. In this paper, we present a CDS application that predicts the probability of having unstable angina based on clinical data. Due to the characteristics of the variables (mostly binary) a Bayesian network model was chosen to support the system. Bayesian-network model was constructed using a population of 1164 patients, and subsequently was validated with a population of 103 patients. The validation results, with a negative predictive value (NPV) of 91%, demonstrate its …
A Method Based on Multi-source Feature Detection for Counting People in Crowded Areas
2019
We propose a crowd counting method for multisource feature fusion. Image features are extracted from multiple sources, and the population is estimated by image feature extraction and texture feature analysis, along with for crowd image edge detection. We count people in high-density still images. For instance, in the city’s squares, sports fields, subway stations, etc. Our approach uses a still image taken by a camera on a drone to appraise the count in the population density image, using a kind of sources of information: HOG, LBP, CANNY. We furnish separate estimates of counts and other statistical measurements through several types of sources. Support vector machine SVM, classification an…
Anomaly Detection in Dynamic Social Systems Using Weak Estimators
2009
Anomaly detection involves identifying observationsthat deviate from the normal behavior of a system. One ofthe ways to achieve this is by identifying the phenomena thatcharacterize “normal” observations. Subsequently, based on thecharacteristics of data learned from the “normal” observations,new observations are classified as being either “normal” or not.Most state-of-the-art approaches, especially those which belongto the family parameterized statistical schemes, work under theassumption that the underlying distributions of the observationsare stationary. That is, they assume that the distributions thatare learned during the training (or learning) phase, thoughunknown, are not time-varyin…
Shared feature representations of LiDAR and optical images: Trading sparsity for semantic discrimination
2015
This paper studies the level of complementary information conveyed by extremely high resolution LiDAR and optical images. We pursue this goal following an indirect approach via unsupervised spatial-spectral feature extraction. We used a recently presented unsupervised convolutional neural network trained to enforce both population and lifetime spar-sity in the feature representation. We derived independent and joint feature representations, and analyzed the sparsity scores and the discriminative power. Interestingly, the obtained results revealed that the RGB+LiDAR representation is no longer sparse, and the derived basis functions merge color and elevation yielding a set of more expressive…
3D inter-subject medical image registration by scatter search
2005
Image registration is a very active research area in computer vision, namely it is used to find a transformation between two images taken under different conditions. Point matching is an image registration approach based on searching for the right pairing of points between the two images. From this matching, the registration transformation we are searching, can be inferred by means of numerical methods. In this paper, we propose a scatter search (SS) algorithm to solve the matching problem. SS is a hybrid metaheuristic with a good trade-off between search space diversification and intensification. On the one hand, diversity is basically introduced from a population-based approach where syst…
Thermographic quantitative variables for diabetic foot assessment: preliminary results
2018
The aim of this study was to define aspects of a protocol for a diabetic population by obtaining and evaluating thermographic images following thermal stress (cooling of the sole of the foot with c...
First record of an established marbled crayfish Procambarus virginalis (Lyko, 2017) population in Estonia
2019
Invasive marbled crayfish Procambarus virginalis (Lyko, 2017) is spreading alarmingly fast across European countries and beyond. Early maturation, parthenogenetic reproduction mode and high growth rate contribute to a high potential invasiveness. Marbled crayfish can pose severe effects on native communities impacting the native crayfish populations being carrier of the crayfish plague disease caused by Aphanomyces astaci. Here we report the first record of marbled crayfish in Estonia. In total, 104 individuals were found in the artificially warm outflow channel of the cooling system of Balti Power Plant, entering to the water reservoir of the River Narva. Molecular analyses confirmed the m…
Fuzzy-based Kernel Regression Approaches for Free Form Deformation and Elastic Registration of Medical Images
2009
In modern medicine, a largely diffused method for gathering knowledge about organs and tissues is obtained by means of merging information from several datasets. Such data are provided from multimodal or sequential acquisitions. As a consequence, a pre-processing step that is called “image registration” is required to achieve data integration. Image registration aims to obtain the best possible spatial correspondence between misaligned datasets. This procedure is also useful to correct distortions induced by magnetic interferences with the acquisition equipment signals or the ones due patient’s involuntary movements such as heartbeat or breathing. The problem can be regarded as finding the …
Instrumental Odour Monitoring System Classification Performance Optimization by Analysis of Different Pattern-Recognition and Feature Extraction Tech…
2020
Instrumental odour monitoring systems (IOMS) are intelligent electronic sensing tools for which the primary application is the generation of odour metrics that are indicators of odour as perceived by human observers. The quality of the odour sensor signal, the mathematical treatment of the acquired data, and the validation of the correlation of the odour metric are key topics to control in order to ensure a robust and reliable measurement. The research presents and discusses the use of different pattern recognition and feature extraction techniques in the elaboration and effectiveness of the odour classification monitoring model (OCMM). The effect of the rise, intermediate, and peak period …