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In this paper, we propose a computational strategy to enhance the performance of Image Quality Metrics (IQM) by using content specific features of an image. We do this by creating Visual Error Importance (VEI) map that is applied to the error maps computed by the IQM. A global optimization can be used to compute the VEI map that is optimal for any given IQM. We demonstrate this concept by categorizing...
Functional connectomes (FCs) are powerful in characterizing brain conditions. Temporal FC metrics can index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior. However, time-varying properties of temporal brain networks in general mental disorders have been less investigated. In this paper, FCs derived from resting-state fMRI (R-fMRI) data are temporally...
One of the greatest challenges for computer science in education is the capacity to provide environments that are intelligent and adaptable to the real needs of students. In order to create efficient adaptive mechanisms for educational content, student models are proposed to identify and to predict the real knowledge level of students. Such models are useful not only for computer systems but also...
Technology is in a constant state of evolution, which allows for new and cunning cyber-attacks and tactics. Out of all these tactics, the exploitation of human cognitive biases in response to phishing attacks is challenging to defend against. The purpose of this study was to determine if humans could discriminate fraudulent Uniform Resource Locators (URLs) or links from legitimate URLs without the...
Research efforts have been devoted to extraction and visualization of vortices in an unsteady (turbulent) flow. Characterizing the behaviors of the flow, vortices are identifiable as regions using a vortex detector known as the lambda2-criterion. Isosurface visualization renders vortex regions based on a chosen isovalue. However, it is highly challenging to choose one isovalue suitable for visualizing...
When looking at an image, humans shift their attention towards interesting regions, making sequences of eye fixations. When describing an image, they also come up with simple sentences that highlight the key elements in the scene. What is the correlation between where people look and what they describe in an image? To investigate this problem, we look into eye fixations and image captions, two types...
This paper investigates visual attention control using the presentation of directional flow stimulus to peripheral vision. Peripheral vision is known to have a superior motion-perception capability. Since central vision is usually used for a primary visual task, it would be quite useful if we could control one's attention by providing assistive information through peripheral motion cues without interfering...
In visually searching for a target symbol out of a number of alternatives, which may include not only symbols from the Latin alphabets but also Arabic, Greek, Chinese, Japanese, Greek, and Russian letters and numerals, and mathematical symbols, the time required to find the target, i.e., the response time, follows Hick's law, which states that the response time is proportional to the logarithm of...
Decision support systems for network security represent a critical element in the safe operation of computer networks. Unfortunately, due to their complexity, it can be difficult to implement and empirically assess novel techniques for displaying networks. This paper details an open source adaptive user interface that hopes to fill this gap. This system supports agile development and offers a wide...
Monocular ORB-SLAM has been proved to be one of the best open-source SLAM method. However, it is still unsatisfying especially in low illumination indoor environment, which is caused by scale recovery and wrong feature matching. In this paper, we proposed a vehicle model based monocular ORBSLAM method supplemented by April-Tag to improve the performance of original algorithm. This approach is practical...
Error-related electroencephalographic (EEG) potentials (ErrPs) have been explored to improve the reliability of modern Brain-Computer Interfaces (BCIs), thanks to the information they carry about user awareness of erroneous responses. ErrPs detection on a single-trial basis has been successfully demonstrated, and proved to effectively enhance human-computer interaction and BCI performance. Previous...
Digital organizations are now ruled by the flexibility offered by remote working environments. The availability of people to work from different places, with digital tools, empower them very often not only to perform their work better and faster, but also to reach higher levels of satisfaction in balancing work and private life. However, from an organizational perspective, there are concerns regarding...
The paper describes human-interactive robot that supports gait training base on autonomous evaluation and navigation of human body movements. Robotic intervention in gait training is a promising method for prospective rehabilitation. In literature, gait training platforms such as power assisting limbs and body supporting mobile platforms have been studied well. These types of platforms, however, mainly...
Salient object detection aims to correctly highlight the most salient object(s) in an image. Combining fine-grained contrast prior with rough-grained object consistency, this paper proposes a Focusness Guided Salient object detection (FGS) algorithm. To obtain clean and precise contrast map, FGS uses the focusness prior to guide the contrast map. Combing different saliency priors, FGS utilizes a unified...
This study present an intervention combining an electroencephalography-based brain computer interface with a hybrid robotic system for the modulation of the cortical excitability (plasticity). Plasticity is intended to be elicited through the association of the voluntary motor-related cortical processes with the hybrid assistance during the execution of reaching movement. The cortical excitability...
Image annotation is an integral and important task for image retrieval. Automatic image annotation has been studied for quite some time now, but there is still enough scope for improvement considering the challenges associated with it. Existing systems focus on reducing the semantic gap between image and text using various heuristic, probabilistic or learning based approaches. Often, the automatic...
With new technologies in the area of assistance and automation on the market, the dream of driving in automated vehicles becomes reality. While certain research areas predict fully autonomous vehicles in the near future, a more feasible composition still has a driver, at least as a back-up solution, operating the vehicle in certain situations with certain degrees of control, cooperating with the automation...
In this paper, a system to aid the visually impaired by providing contextual information of the surroundings using 360° view camera combined with deep learning is proposed. The system uses a 360° view camera with a mobile device to capture surrounding scene information and provide contextual information to the user in the form of audio. The scene information from the spherical camera feed is classified...
In this paper, we experimentally examine the relationship between visual cognition difficulty and target-tracking eye movements, which recorded during moving target cognition. Generally, such eye movements are observed when humans perceive a moving object and they vary widely due to many factors, such as target shape, backgrounds, illumination conditions, and so on. Several systems have been proposed...
Patients with disorders of consciousness (DOC) cannot reply to questions or clinical assessments using voluntary motor control, and therefore it is very difficult to assess their cognitive capabilities and conscious awareness. Patients who are locked-in (LIS) are instead fully conscious, and they can communicate with their preserved eye movements. However, when the residual oculomotor activity is...
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