No-reference color-depth quality measure: CDME

2018 ◽  
Author(s):  
Srijith Rajeev ◽  
Karen Panetta ◽  
Sos S. Agaian
Keyword(s):  
Quality Measure ◽  
Color Depth

Quintessenz

2016 ◽  
Vol 1 (2) ◽  
pp. 47-49
Author(s):  
Anja Maria Reichel
Keyword(s):  
Psychiatric Treatment ◽  
Quality Measure ◽  
Psychiatric Nurses ◽  
Patient Centered ◽  
Inpatient Psychiatric Treatment

Zusammenfassung. Delaney, K. R., Johnson, M. E. and Fogg, L. (2015): Development and Testing of the Combined Assessment of Psychiatric Environments: A Patient-Centered Quality Measure for Inpatient Psychiatric Treatment. Journal of the American Psychiatric Nurses Association, 21 (2), 134–147.

Maximum Allowable Proportion Defective (MAPD) --- A Quality Measure

2011 ◽  
Vol 3 (6) ◽  
pp. 524-525
Author(s):  
Ramkumar.T.B Ramkumar.T.B ◽  
Keyword(s):  
Quality Measure

scholarly journals Iranian kinect face database (IKFDB): a color-depth based face database collected by kinect v.2 sensor

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Seyed Muhammad Hossein Mousavi ◽  
S. Younes Mirinezhad
Keyword(s):  
Neural Network ◽  
Facial Expression ◽  
Facial Expression Recognition ◽  
Depth Image ◽  
Sensor Technology ◽  
Support Vector ◽  
Expression Recognition ◽  
Face Database ◽  
Depth Data ◽  
Color Depth

AbstractThis study presents a new color-depth based face database gathered from different genders and age ranges from Iranian subjects. Using suitable databases, it is possible to validate and assess available methods in different research fields. This database has application in different fields such as face recognition, age estimation and Facial Expression Recognition and Facial Micro Expressions Recognition. Image databases based on their size and resolution are mostly large. Color images usually consist of three channels namely Red, Green and Blue. But in the last decade, another aspect of image type has emerged, named “depth image”. Depth images are used in calculating range and distance between objects and the sensor. Depending on the depth sensor technology, it is possible to acquire range data differently. Kinect sensor version 2 is capable of acquiring color and depth data simultaneously. Facial expression recognition is an important field in image processing, which has multiple uses from animation to psychology. Currently, there is a few numbers of color-depth (RGB-D) facial micro expressions recognition databases existing. With adding depth data to color data, the accuracy of final recognition will be increased. Due to the shortage of color-depth based facial expression databases and some weakness in available ones, a new and almost perfect RGB-D face database is presented in this paper, covering Middle-Eastern face type. In the validation section, the database will be compared with some famous benchmark face databases. For evaluation, Histogram Oriented Gradients features are extracted, and classification algorithms such as Support Vector Machine, Multi-Layer Neural Network and a deep learning method, called Convolutional Neural Network or are employed. The results are so promising.

Safety and quality measure audit in an organisation – A case study

2021 ◽  
Author(s):  
P. Nagaveni ◽  
A. Amudha ◽  
M. Siva Ramkumar ◽  
G. Emayavaramban ◽  
S. Divyapriya ◽  
...  
Keyword(s):  
Quality Measure

scholarly journals Evaluation of Pulmonary Embolism in the Emergency Department and Consistency With a National Quality Measure

2012 ◽  
Vol 172 (13) ◽  
Author(s):  
Arjun K. Venkatesh ◽  
Jeffrey A. Kline ◽  
D. Mark Courtney ◽  
Carlos A. Camargo ◽  
Michael C. Plewa ◽  
...  
Keyword(s):  
Emergency Department ◽  
Pulmonary Embolism ◽  
Quality Measure ◽  
National Quality
Sign in / Sign up

Export Citation Format

Share Document