Atmospheric Characterization During Super-Resolution Vision System Developmental Testing

2013 ◽  
Author(s):  
M. S. D'Arcy ◽  
David Tofsted ◽  
Edward Creegan ◽  
Robert Brice
Keyword(s):  
Vision System ◽  
Super Resolution

ADAS Vision System with Video Super Resolution

2021 ◽  
pp. 135-148
Author(s):  
Mrunmayee V. Daithankar ◽  
Sachin D. Ruikar
Keyword(s):  
Vision System ◽  
Super Resolution

DARPA super resolution vision system (SRVS) robust turbulence data collection and analysis

2014 ◽  
Author(s):  
Richard L. Espinola ◽  
Kevin R. Leonard ◽  
Roger Thompson ◽  
David Tofsted ◽  
Sean D'Arcy
Keyword(s):  
Data Collection ◽  
Vision System ◽  
Super Resolution ◽  
Data Collection And Analysis ◽  
Turbulence Data

scholarly journals GAN-Based Image Super-Resolution with a Novel Quality Loss

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xining Zhu ◽  
Lin Zhang ◽  
Lijun Zhang ◽  
Xiao Liu ◽  
Ying Shen ◽  
...  
Keyword(s):  
Image Quality Assessment ◽  
Vision System ◽  
Super Resolution ◽  
Human Vision ◽  
Generative Adversarial Networks ◽  
Quality Loss ◽  
Adversarial Networks ◽  
Image Super Resolution ◽  
Single Image Super Resolution ◽  
First Time

Single image super-resolution (SISR) has been a very attractive research topic in recent years. Breakthroughs in SISR have been achieved due to deep learning and generative adversarial networks (GANs). However, the generated image still suffers from undesired artifacts. In this paper, we propose a new method named GMGAN for SISR tasks. In this method, to generate images more in line with human vision system (HVS), we design a quality loss by integrating an image quality assessment (IQA) metric named gradient magnitude similarity deviation (GMSD). To our knowledge, it is the first time to truly integrate an IQA metric into SISR. Moreover, to overcome the instability of the original GAN, we use a variant of GANs named improved training of Wasserstein GANs (WGAN-GP). Besides GMGAN, we highlight the importance of training datasets. Experiments show that GMGAN with quality loss and WGAN-GP can generate visually appealing results and set a new state of the art. In addition, large quantity of high-quality training images with rich textures can benefit the results.

A closed-loop, ACT-R approach to modeling approach and landing with and without synthetic vision system (SVS) technology

2004 ◽  
Author(s):  
Michael D. Byrne ◽  
Alex Kirlik ◽  
Michael D. Fleetwood ◽  
David G. Huss ◽  
Alex Kosorukoff ◽  
...  
Keyword(s):  
Closed Loop ◽  
Vision System ◽  
Modeling Approach ◽  
Synthetic Vision

SVM-based global vision system of sports competition and action recognition

2020 ◽  
pp. 1-12
Author(s):  
Changxin Sun ◽  
Di Ma
Keyword(s):  
Target Recognition ◽  
Vision System ◽  
Task Assignment ◽  
Recognition Algorithm ◽  
Control Factor ◽  
Training Time ◽  
Adaboost Algorithm ◽  
Advantages And Disadvantages ◽  
Time Control ◽  
Correlation Degree

In the research of intelligent sports vision systems, the stability and accuracy of vision system target recognition, the reasonable effectiveness of task assignment, and the advantages and disadvantages of path planning are the key factors for the vision system to successfully perform tasks. Aiming at the problem of target recognition errors caused by uneven brightness and mutations in sports competition, a dynamic template mechanism is proposed. In the target recognition algorithm, the correlation degree of data feature changes is fully considered, and the time control factor is introduced when using SVM for classification,At the same time, this study uses an unsupervised clustering method to design a classification strategy to achieve rapid target discrimination when the environmental brightness changes, which improves the accuracy of recognition. In addition, the Adaboost algorithm is selected as the machine learning method, and the algorithm is optimized from the aspects of fast feature selection and double threshold decision, which effectively improves the training time of the classifier. Finally, for complex human poses and partially occluded human targets, this paper proposes to express the entire human body through multiple parts. The experimental results show that this method can be used to detect sports players with multiple poses and partial occlusions in complex backgrounds and provides an effective technical means for detecting sports competition action characteristics in complex backgrounds.

Modern Technology for Image processing and Computer vision -A Review

2018 ◽  
Vol 1 (2) ◽  
pp. 17-23
Author(s):  
Takialddin Al Smadi
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Augmented Reality ◽  
Video Compression ◽  
Video Processing ◽  
Vision System ◽  
Citrus Fruit ◽  
Modern Technology ◽  
Image And Video Processing ◽  
Depth Video

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality.   © 2018 JASET, International Scholars and Researchers Association

Super-Resolution Microscopy in Studying the Structure and Function of the Cell Nucleus

Acta Naturae ◽  
2017 ◽  
Vol 9 (4) ◽  
pp. 42-51
Author(s):  
S. S. Ryabichko ◽  
◽  
A. N. Ibragimov ◽  
L. A. Lebedeva ◽  
E. N. Kozlov ◽  
...  
Keyword(s):  
Cell Nucleus ◽  
Super Resolution ◽  
Structure And Function ◽  
And Function ◽  
Super Resolution Microscopy
Sign in / Sign up

Export Citation Format

Share Document