scholarly journals CNN-based People Detection in Voxel Space using Intensity Measurements and Point Cluster Flattening

2021 ◽  
Vol 42 (2) ◽  
pp. 37-46
Author(s):  
Joacim Dybedal ◽  
Geir Hovland
Keyword(s):  
People Detection ◽  
Intensity Measurements ◽  
Voxel Space

Thickness and composition determinations from T.E.M. specimens using both x-ray and backscattered electron data

1984 ◽  
Vol 42 ◽  
pp. 576-577
Author(s):  
M.D. Ball ◽  
H. Lagace ◽  
M.C. Thornton
Keyword(s):  
Electron Microscope ◽  
Atomic Number ◽  
Transmission Electron Microscope ◽  
Convenient Method ◽  
Flow Chart ◽  
X Ray ◽  
Intensity Measurements ◽  
Transmission Electron ◽  
Electron Intensity ◽  
Backscattered Electron

The backscattered electron coefficient η for transmission electron microscope specimens depends on both the atomic number Z and the thickness t. Hence for specimens of known atomic number, the thickness can be determined from backscattered electron coefficient measurements. This work describes a simple and convenient method of estimating the thickness and the corrected composition of areas of uncertain atomic number by combining x-ray microanalysis and backscattered electron intensity measurements.The method is best described in terms of the flow chart shown In Figure 1. Having selected a feature of interest, x-ray microanalysis data is recorded and used to estimate the composition. At this stage thickness corrections for absorption and fluorescence are not performed.

The Mechanical Response of Aligned Carbon Nanotube Mats via Transmitted Laser Intensity Measurements

2008 ◽  
Author(s):  
Christian Deck ◽  
Chinung Ni ◽  
Kenneth Vecchio ◽  
Prabhakar Bandaru
Keyword(s):  
Carbon Nanotube ◽  
Mechanical Response ◽  
Laser Intensity ◽  
Intensity Measurements

The Special Features of Radar Developments for People Detection under Obstructions

2004 ◽  
Vol 61 (7-12) ◽  
pp. 875-893 ◽  
Author(s):  
I. A. Vyazmitinov ◽  
Ye. I. Myroshnychenko ◽  
O. V. Sytnik
Keyword(s):  
People Detection

scholarly journals Smart Video Surveillance System Based on Edge Computing

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2958
Author(s):  
Antonio Carlos Cob-Parro ◽  
Cristina Losada-Gutiérrez ◽  
Marta Marrón-Romera ◽  
Alfredo Gardel-Vicente ◽  
Ignacio Bravo-Muñoz
Keyword(s):  
Computer Vision ◽  
Video Surveillance ◽  
Surveillance System ◽  
Video Surveillance System ◽  
Smart Camera ◽  
People Detection ◽  
Camera System ◽  
Edge Node ◽  
New Processing ◽  
Processor Unit

New processing methods based on artificial intelligence (AI) and deep learning are replacing traditional computer vision algorithms. The more advanced systems can process huge amounts of data in large computing facilities. In contrast, this paper presents a smart video surveillance system executing AI algorithms in low power consumption embedded devices. The computer vision algorithm, typical for surveillance applications, aims to detect, count and track people’s movements in the area. This application requires a distributed smart camera system. The proposed AI application allows detecting people in the surveillance area using a MobileNet-SSD architecture. In addition, using a robust Kalman filter bank, the algorithm can keep track of people in the video also providing people counting information. The detection results are excellent considering the constraints imposed on the process. The selected architecture for the edge node is based on a UpSquared2 device that includes a vision processor unit (VPU) capable of accelerating the AI CNN inference. The results section provides information about the image processing time when multiple video cameras are connected to the same edge node, people detection precision and recall curves, and the energy consumption of the system. The discussion of results shows the usefulness of deploying this smart camera node throughout a distributed surveillance system.

scholarly journals Airglow Measurements of Gravity Wave Propagation and Damping over Kolhapur (16.5°N, 74.2°E)

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
R. N. Ghodpage ◽  
A. Taori ◽  
P. T. Patil ◽  
S. Gurubaran ◽  
A. K. Sharma ◽  
...  
Keyword(s):  
Wave Propagation ◽  
Gravity Wave ◽  
Meridional Wind ◽  
Vertical Wavelength ◽  
Emission Layer ◽  
Positive Correlation ◽  
Intensity Measurements ◽  
Wind Shears ◽  
The Waves ◽  
Airglow Intensity

Simultaneous mesospheric OH and O  (1S) night airglow intensity measurements from Kolhapur (16.8°N, 74.2°E) reveal unambiguous gravity wave signatures with periods varying from 01 hr to 9 hr with upward propagation. The amplitudes growth of these waves is found to vary from 0.4 to 2.2 while propagating from the OH layer (~87 km) to the O (1S) layer (~97 km). We find that vertical wavelength of the observed waves increases with the wave period. The damping factors calculated for the observed waves show large variations and that most of these waves were damped while traveling from the OH emission layer to the O (1S) emission layer. The damping factors for the waves show a positive correlation at vertical wavelengths shorter than 40 km, while a negative correlation at higher vertical wavelengths. We note that the damping factors have stronger positive correlation with meridional wind shears compared to the zonal wind shears.

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