42 research outputs found
A Real-Time Ball Detection Approach Using Convolutional Neural Networks
Ball detection is one of the most important tasks in the context of soccer-playing robots. The ball is a small moving object which can be blurred and occluded in many situations. Several neural network based methods with different architectures are proposed to deal with the ball detection. However, they are either neglecting to consider the computationally low resources of humanoid robots or highly depend on manually-tuned heuristic methods to extract the ball candidates. In this paper, we propose a new ball detection method for low-cost humanoid robots that can detect most soccer balls with a high accuracy rate of up to 97.17%. The proposed method is divided into two steps. First, some coarse regions that may contain a full ball are extracted using an iterative method employing an efficient integral image based feature. Then they are fed to a light-weight convolutional neural network to finalize the bounding box of a ball. We have evaluated the proposed approach using a comprehensive dataset and the experimental results show the efficiency of our method
Anxiety disorders in headache patients in a specialised clinic: prevalence and symptoms in comparison to patients in a general neurological clinic
Data from several studies indicate an association of headache with anxiety disorders. In this study, we assessed and differentiated anxiety disorders in 100 headache patients by using the PSWQ (Penn State Worry Questionnaire) screening tool for generalised anxiety disorder (GAD) and the ACQ (Agoraphobic Cognitions Questionnaire) and BSQ (Body Sensation Questionnaire) for panic disorder (PD). Control groups were constructed: (1) on the basis of epidemiological studies on PD and GAD in the general population and (2) by including neurological patients. 37.0% of headache patients had a GAD. 27% of headache patients met the score for PD in the BSQ, 4.0% in the ACQ. Significant results were obtained in comparison to the general population (p < 0.001) and with regard to GAD in comparison with a sample of neurological patients (p < 0.005). The BSQ significantly correlated with the number of medication days (p < 0.005). The results confirm the increased prevalence of GAD in headache patients. PD seems to increase the risk of medication overuse
Information Display Protocol
Objective: Human Factors Engineers and air traffic control Subject Matter Experts (SMEs) from the Federal Aviation Administration (FAA) developed a protocol to support in decisions on how to present needed information on the en route controller\u2019s visual displays. The protocol provides guidance for determining the criticality of the information and uses this criticality to determine where and how the information should be displayed. Background: Human Factors Engineers and air traffic control SMEs developed and validated the protocol with current and upcoming FAA Next Generation Air Transportation System informational items and scenarios. Application: The model provides a systematic method for integrating the informational needs of controllers and supports the decision process for designing air traffic control displays