On the Effect of Sensing-holes in PIR-based Occupancy Detection Systems

2016 ◽  
Author(s):  
Abdelraouf Ouadjaout ◽  
Noureddine Lasla ◽  
Djamel Djenouri ◽  
Cherif Zizoua
Keyword(s):  
Detection Systems ◽  
Occupancy Detection

scholarly journals Generalized Parking Occupancy Analysis Based on Dilated Convolutional Neural Network

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 277 ◽  
Author(s):  
Sherzod Nurullayev ◽  
Sang-Woong Lee
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Traffic Congestion ◽  
Parking Space ◽  
Urban Centers ◽  
Detection Systems ◽  
Perspective Distortion ◽  
Occupancy Detection ◽  
Parking Lot ◽  
Parking Space Detection

The importance of vacant parking space detection systems is increasing dramatically as the avoidance of traffic congestion and the time-consuming process of searching an empty parking space is a crucial problem for drivers in urban centers. However, the existing parking space occupancy detection systems are either hardware expensive or not well-generalized for varying images captured from different camera views. As a solution, we take advantage of an affordable visual detection method that is made possible by the fact that camera monitoring is already available in the majority of parking areas. However, the current problem is a challenging vision task because of outdoor lighting variation, perspective distortion, occlusions, different camera viewpoints, and the changes due to the various seasons of the year. To overcome these obstacles, we propose an approach based on Dilated Convolutional Neural Network specifically designed for detecting parking space occupancy in a parking lot, given only an image of a single parking spot as input. To evaluate our method and allow its comparison with previous strategies, we trained and tested it on well-known publicly available datasets, PKLot and CNRPark + EXT. In these datasets, the parking lot images are already labeled, and therefore, we did not need to label them manually. The proposed method shows more reliability than prior works especially when we test it on a completely different subset of images. Considering that in previous studies the performance of the methods was compared with well-known architecture—AlexNet, which shows a highly promising achievement, we also assessed our model in comparison with AlexNet. Our investigations showed that, in comparison with previous approaches, for the task of classifying given parking spaces as vacant or occupied, the proposed approach is more robust, stable, and well-generalized for unseen images captured from completely different camera viewpoints, which has strong indications that it would generalize effectively to other parking lots.

The Potentials of Scanning Microscopy

1968 ◽  
Vol 26 ◽  
pp. 352-353
Author(s):  
A. V. Crewe
Keyword(s):  
Salient Feature ◽  
Secondary Emission ◽  
Resolving Power ◽  
X Rays ◽  
Scanning Microscope ◽  
Forming Process ◽  
Additional Tool ◽  
Detection Systems ◽  
Conventional Microscope ◽  
Present Information

If the resolving power of a scanning electron microscope can be improved until it is comparable to that of a conventional microscope, it would serve as a valuable additional tool in many investigations.The salient feature of scanning microscopes is that the image-forming process takes place before the electrons strike the specimen. This means that several different detection systems can be employed in order to present information about the specimen. In our own particular work we have concentrated on the use of energy loss information in the beam which is transmitted through the specimen, but there are also numerous other possibilities (such as secondary emission, generation of X-rays, and cathode luminescence).Another difference between the pictures one would obtain from the scanning microscope and those obtained from a conventional microscope is that the diffraction phenomena are totally different. The only diffraction phenomena which would be seen in the scanning microscope are those which exist in the beam itself, and not those produced by the specimen.

Universal ESEM

1993 ◽  
Vol 51 ◽  
pp. 786-787
Author(s):  
G.D. Danilatos
Keyword(s):  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
High Vacuum ◽  
Natural Extension ◽  
Necessary Condition ◽  
Environmental Scanning ◽  
Detection Systems ◽  
Small Gain ◽  
Detection Medium ◽  
Scanning Electron

The environmental scanning electron microscope (ESEM) has evolved as the natural extension of the scanning electron microscope (SEM), both historically and technologically. ESEM allows the introduction of a gaseous environment in the specimen chamber, whereas SEM operates in vacuum. One of the detection systems in ESEM, namely, the gaseous detection device (GDD) is based on the presence of gas as a detection medium. This might be interpreted as a necessary condition for the ESEM to remain operational and, hence, one might have to change instruments for operation at low or high vacuum. Initially, we may maintain the presence of a conventional secondary electron (E-T) detector in a "stand-by" position to switch on when the vacuum becomes satisfactory for its operation. However, the "rough" or "low vacuum" range of pressure may still be considered as inaccessible by both the GDD and the E-T detector, because the former has presumably very small gain and the latter still breaks down.

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