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This paper introduces a novel approach for modeling visual relations between pairs of objects. We call relation a triplet of the form (subject; predicate; object) where the predicate is typically a preposition (eg. ’under’, ’in front of’) or a verb (’hold’, ’ride’) that links a pair of objects (subject; object). Learning such relations is challenging as the objects have different spatial configurations...
The use of cognitive maps in support of solving practical problems of analysis of ill-structured situations and large-scale systems in economics, medicine, ecology, education and military-political sphere is growing. The problem of visual perception and understanding of cognitive maps is proven to be extremely urgent and practically important. The set of visualization methods that provide better perception...
The tonic postural system guarantees the stability of the human body in upright stance and during locomotion. It is considered as a complex organization which involves several internal systems and has multiple sources of information. In this paper, we provide a review of techniques and materials for human stability assessment. The primary tools to record and evaluate human sways in static posture...
The Leopold and Rudolf Blaschka replicas of ma- rine invertebrates are among the more famous objects produced in the XIXth century for pedagogical purposes. Their high level of detail, still unknown manufacturing technique and their con- ceived artistic beauty, make these glass replicas precious museum exhibits currently. The fragility of these items produced by the Blaschka family (father and son)...
We report an experimental study that involves understanding how display (conventional or ecological) and system mode (profiting, neutral or losing) affect financial trading performance and risk preference. Twenty-four undergraduate and graduate student participants interacted with a financial trading simulator in the playback of a real market. Each participant completed a conventional display scenario...
In a recent past, several techniques have been developed to analyze the events contained in the electrohysterogram signals (EHG). But, the most of them focused on offline methods. In this study, we use an online method which is developed previously and known by Dynamic Cumulative Sum (DCS). The approach is applied on real EHG signals database through a 4×4 electrodes matrix. For this purpose, two...
Convolutional Neural Networks (CNN) have been regarded as a powerful class of models for image recognition problems. Nevertheless, it is not trivial when utilizing a CNN for learning spatio-temporal video representation. A few studies have shown that performing 3D convolutions is a rewarding approach to capture both spatial and temporal dimensions in videos. However, the development of a very deep...
For the image of present surface defects in steel plates, a surface defect detection method based on human visual attention mechanism is proposed. Based on the physiological structure and function of human visual system, this paper establishes a steel surface defect detection model via Gaussian filter, Gabor filter and the calculation such as cross-scale reduction, cross-scale addition and normalization,...
2D Gabor filters are sinusoidal waves of some frequency and orientation within a 2D Gaussian envelope and are used to model simple cells (S1) in primate visual cortex. Visual system in primates extracts information both in 2D spatial and frequency domains. In this paper, we use multiple spatial frequencies to model S1 cells in primates visual cortex. Thereafter, we use MAX and STD operators to extract...
Visualization is a flexible way to analyze simulated data and serves as a means for scientific discovery. Large scale neural simulations using high performance and distributed computing techniques produce huge amount of data for which visual analysis is generally difficult to perform. In this paper, a spiking neuron simulation environment was created to model and simulate networks of neurons of the...
The paper is devoted to modeling of single-layer garments as developable median surfaces, modeled in the form of a thin supple shell. The products are modeled in Maple 9.5 and Embarcadero RAD Studio. The modelling of conical skirts considering seams is performed to demonstrate the space form of garments in the gravity field of elastic materials. Also the product aeroman is modelled which brings the...
Biometric authentication systems verify the identity of individuals based on what they are. As they are error prone, they can reject genuine individuals or accept impostors. Researchers of the field quantify the quality of their algorithm by benchmarking it on several databases. However, although the standard evaluation metrics state the performance of their system, they are unable to explain the...
In this paper, we propose to incorporate convolutional neural networks with a multi-context attention mechanism into an end-to-end framework for human pose estimation. We adopt stacked hourglass networks to generate attention maps from features at multiple resolutions with various semantics. The Conditional Random Field (CRF) is utilized to model the correlations among neighboring regions in the attention...
Studies in visual perceptual learning investigate the way human performance improves with practice, in the context of relatively simple (and therefore more manageable) visual tasks. Building on the powerful tools currently available for the training of Convolution Neural Networks (CNN), networks whose original architecture was inspired by the visual system, we revisited some of the open computational...
Business process variability is an active research area in the field of business process management and deals with variations and commonalities among processes of a given process family. Many theoretical approaches have been suggested in the last years; however, practical implementations are rare and limited in their functionality. In this paper, we propose a new approach for business process variability...
Although the area of surgical simulation has been the subject of study in recent years, it is still necessary to develop artificial experimental models with a perspective to dismiss the use of biological models. Since this makes the simulators more real, transferring the environment of the health professional to a physical or virtual reality, an anesthetic prototype has been developed, where the motor...
This paper presents an original framework based on deep learning and preference learning to retrieve and characterize biomedical images for assisting physicians in diagnosing complex diseases with potentially only small differences between them. In particular, we use deep learning to extract the high-level and compact features for biomedical images. In contrast to the traditional biomedical algorithms...
With the advent of the Internet and the growth in the use of cyberspace by consumers for online healthcare information (OHI), various researchers from different disciplines have been working on the challenges and threats posed by the issue of cyberchondria, which is related to the cyber psychological aspects of uncertainty, anxiety, quality, and credibility. However, there are few research efforts,...
This paper deals with the creation of the behavior model and the model of the biological-psychical state of the fighting pilot. Creating of the biological-psychical state model of the pilot is a part of the research activities on the Air Force and Air Technology Department. The aim of the project is to solve the role of the pilot in the interface human — machine (pilot — fighter). Using of the adaptable...
Perception of spatial coherence and boundaries for the fusion of spatially incoherent stimuli in the context of multimedia reproduction have mainly been studied with continuous judgment scales. As results vary greatly between different studies, reaction time measurements are proposed as an indirect measure of the perception of spatial incoherence. Word recognition tasks for spatially coherent and...
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