scholarly journals Low-diffusion Xe-He gas mixtures for rare-event detection: electroluminescence yield

2020 ◽  
Vol 2020 (4) ◽  
Author(s):  
A. F. M. Fernandes ◽  
◽  
C. A. O. Henriques ◽  
R. D. P. Mano ◽  
D. González-Díaz ◽  
...  
Keyword(s):  
Event Detection ◽  
Rare Event ◽  
Gas Mixtures

scholarly journals New gas mixtures suitable for rare event detection using a Micromegas-TPC detector

2009 ◽  
Vol 4 (01) ◽  
pp. P01001-P01001 ◽  
Author(s):  
L Ounalli ◽  
J-L Vuilleumier ◽  
D Schenker ◽  
J -M Vuilleumier
Keyword(s):  
Event Detection ◽  
Rare Event ◽  
Gas Mixtures

Framework for rare event detection using Artificial Neural Network based context free grammar

2020 ◽  
Vol 39 (6) ◽  
pp. 8463-8475
Author(s):  
Palanivel Srinivasan ◽  
Manivannan Doraipandian
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Event Detection ◽  
Performance Metrics ◽  
Rare Events ◽  
Rare Event ◽  
Video Stream ◽  
Context Free Grammar ◽  
Artificial Neural ◽  
Context Free

Rare event detections are performed using spatial domain and frequency domain-based procedures. Omnipresent surveillance camera footages are increasing exponentially due course the time. Monitoring all the events manually is an insignificant and more time-consuming process. Therefore, an automated rare event detection contrivance is required to make this process manageable. In this work, a Context-Free Grammar (CFG) is developed for detecting rare events from a video stream and Artificial Neural Network (ANN) is used to train CFG. A set of dedicated algorithms are used to perform frame split process, edge detection, background subtraction and convert the processed data into CFG. The developed CFG is converted into nodes and edges to form a graph. The graph is given to the input layer of an ANN to classify normal and rare event classes. Graph derived from CFG using input video stream is used to train ANN Further the performance of developed Artificial Neural Network Based Context-Free Grammar – Rare Event Detection (ACFG-RED) is compared with other existing techniques and performance metrics such as accuracy, precision, sensitivity, recall, average processing time and average processing power are used for performance estimation and analyzed. Better performance metrics values have been observed for the ANN-CFG model compared with other techniques. The developed model will provide a better solution in detecting rare events using video streams.

scholarly journals Setting objective thresholds for rare event detection in flow cytometry

2014 ◽  
Vol 409 ◽  
pp. 54-61 ◽  
Author(s):  
Adam J. Richards ◽  
Janet Staats ◽  
Jennifer Enzor ◽  
Katherine McKinnon ◽  
Jacob Frelinger ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Event Detection ◽  
Rare Event

scholarly journals Use of fluorescence threshold triggering and high-speed flow cytometry for rare event detection

Cytometry ◽  
1995 ◽  
Vol 22 (4) ◽  
pp. 317-322 ◽  
Author(s):  
Mark A. Rehse ◽  
Stan Corpuz ◽  
Shelly Heimfeld ◽  
Mark Minie ◽  
Diane Yachimiak
Keyword(s):  
Flow Cytometry ◽  
Event Detection ◽  
High Speed ◽  
Rare Event ◽  
High Speed Flow ◽  
Speed Flow

scholarly journals 7th International Symposium on Large TPCs for Low-Energy Rare Event Detection

2015 ◽  
Vol 650 ◽  
pp. 011001
Author(s):  
P Colas ◽  
I Giomataris ◽  
I Irastorza ◽  
Th Patzak
Keyword(s):  
International Symposium ◽  
Event Detection ◽  
Rare Event ◽  
Low Energy

scholarly journals Strategies for Rare-Event Detection: An Approach for Automated Fetal Cell Detection in Maternal Blood

1998 ◽  
Vol 63 (6) ◽  
pp. 1783-1792 ◽  
Author(s):  
Jan C. Oosterwijk ◽  
Cecile F.H.M. Knepflé ◽  
Wilma E. Mesker ◽  
Hans Vrolijk ◽  
Willem C.R. Sloos ◽  
...  
Keyword(s):  
Event Detection ◽  
Rare Event ◽  
Maternal Blood ◽  
Cell Detection ◽  
Fetal Cell

Rare Event Detection and Propagation in Wireless Sensor Networks

2016 ◽  
Vol 48 (4) ◽  
pp. 1-22 ◽  
Author(s):  
David C. Harrison ◽  
Winston K. G. Seah ◽  
Ramesh Rayudu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Event Detection ◽  
Rare Event ◽  
Wireless Sensor

scholarly journals A digital image microscopy system for rare-event detection using fluorescent probes

Cytometry ◽  
1989 ◽  
Vol 10 (3) ◽  
pp. 256-262 ◽  
Author(s):  
Benjamin R. Lee ◽  
David B. Haseman ◽  
C. Patrick Reynolds
Keyword(s):  
Digital Image ◽  
Fluorescent Probes ◽  
Event Detection ◽  
Rare Event
Sign in / Sign up

Export Citation Format

Share Document