Abstract Vortex cores in fluid mechanics are easy to visualize, yet difficult detect numerically. Precise knowledge of these allows dynamics researchers study complex flow structures and allow for a better understanding the turbulence transition process development evolution instabilities, name but few relevant areas. Various approaches such as Q, delta, swirling strength criterion have been pr...

Due to the increasing calculation power of dedicated hardware, real-time image processing becomes practicable at reasonable expenses. Nevertheless the algorithms concerned have to be adapted to real-time requirements. The subject treated in this paper is tie detection for automated railway inspection. An edge detector is proposed in which the sensitivity is adaptable to the local brightness of ...

Robust tracking and segmentation of faces is a prerequisite for face analysis and recognition. In this paper, we describe an approach to this problem which is well suited to surveillance applications with poorly constrained viewing conditions. It integrates motion-based tracking with modelbased face detection to produce segmented face sequences from complex scenes containing several people. The...

SSD [18] is one of the state-of-the-art object detection algorithms, and it combines high detection accuracy with real-time speed. However, it is widely recognized that SSD is less accurate in detecting small objects compared to large objects, because it ignores the context from outside the proposal boxes. In this paper, we present CSSD– a shorthand for context-aware single-shot multibox object...

An extension of second-order diierential edge detection methods to color images was previously proposed. This work shows how, by casting the problem into a subpixel resolution oriented framework, an eecient algorithm for edge detection and contour traversal can be devised for both graylevel and color images. The results from an implementation on a standard PC show that the computational cost is...

Video-based vehicle detection has received considerable attention over the last ten years and there are many deep learning based detection methods which can be utilized to solve the problem. However, these methods are devised for still images and applying them for video vehicle detection directly always obtain poor performance. In this work, we propose a new one-stage video-based vehicle detect...

The network infrastructure has evolved rapidly due to the ever-increasing volume of users and data. massive number online devices forced transform facilitate operational necessities consumers. Among these necessities, security is prime significance. Network intrusion detection systems (NIDS) are among most suitable approaches detect anomalies assaults on a network. However, keeping up with requ...

background: several studies have showed an increased prevalence of airflow obstruction in first degree relatives of individuals with chronic obstructive pulmonary disease (copd). considering no specific research had evaluated airway resistance in offspring of patients with severe copd, we utilized a spirometry and a impulse oscillometry (io) to evaluate this population. materials and methods: i...

Most of the recent successful methods in accurate object detection utilized some variants of R-CNN style two stage Convolutional Neural Networks (CNN) in which plausible regions were proposed in the first stage followed by a second stage for decision refinement. These methods are accurate but hard and slow to train. Single stage detection methods, on the other hand, enjoy the high speed of trai...