Development of Prototype Video-Based Sensor for Vehicle Detection from Stand-Still Images

1997 ◽  
Vol 1570 (1) ◽  
pp. 202-210
Author(s):  
Anthony Tzes ◽  
William R. McShane
Keyword(s):  
Detection System ◽  
A Priori ◽  
Vehicle Detection ◽  
Field Studies ◽  
Wide Area ◽  
Prototype System ◽  
Design Development ◽  
Still Images ◽  
Observation Area ◽  
Traffic Detection

The design, development, and testing of a prototype wide-area traffic detection system are described. The video-based sensor computes the approximate number of vehicles present within an a priori defined observation area from stand-still images. This sensor is mostly oriented toward the traffic detection in congested intersections, in which sensors using existing radar, acoustic, and video-based technology are faced with critical obstacles caused by the automobile stoppage. The prototype system has been tested and found to perform satisfactorily in field studies.

Acoustic Signal Based Automatic Vehicle Detection System

2012 ◽  
Vol 2 (4) ◽  
pp. 88-89
Author(s):  
Sai Sandeep.k Sai Sandeep.k ◽  
◽  
P. Vijay Kumar
Keyword(s):  
Acoustic Signal ◽  
Detection System ◽  
Vehicle Detection

Biological invasions: are they dependent on disturbance?

1997 ◽  
Vol 5 (2) ◽  
pp. 131-144 ◽  
Author(s):  
J D Lozon ◽  
H J MacIsaac
Keyword(s):  
Exotic Species ◽  
Human Activities ◽  
Water Discharge ◽  
A Priori ◽  
Terrestrial Ecosystems ◽  
Field Studies ◽  
Soil Disturbance ◽  
Exotic Animals ◽  
Introduced Plants ◽  
Disturbed Habitats

We utilize literature surveys to examine the relationship between establishment of exotic species and human or natural disturbances of ecosystems. Of the 133 papers published in 10 ecological journals between 1993 and 1995, 63 reported on field studies involving 299 and 103 successful, nonredundant plant and animal introductions, respectively. Invasions of terrestrial ecosystems dominated (>>97%) the surveyed literature. Disturbance was associated with establishment of exotic species in 56% of these studies, though its importance differed among papers describing plants (68%) and animals (28%). Plants species (86%) were significantly more dependent on disturbance for establishment than were animals (12%). However, animals and plants that were dependent on disturbance for establishment were almost equally dependent (58 versus 68%) on it for range expansion. In a second survey, 402 plant and 103 animal taxa were identified that explicitly linked establishment of exotic species to disturbance. Human activities were attributed with establishment of species in 97 and 57% of these cases, respectively. Common mechanisms associated with establishment of exotic animals included ballast water discharge, intentional releases, and residential development. Establishment of exotic plants was associated with animal activities (e.g., grazing, seed introduction), soil disturbance, forestry, fire, agriculture, and human activities. In contrast to invasions theory, our survey indicates that the association between establishment and spread of exotic species and disturbance ought not be assumed a priori. Some animals repeatedly invade new habitats once geographic barriers are circumvented, indicating that communities may be more receptive to exotic species than previously acknowledged. By contrast, introduced plants established most often in disturbed habitats.

scholarly journals Cost-Sensitive Approach to Improve the HTTP Traffic Detection Performance on Imbalanced Data

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Wenmin Li ◽  
Sanqi Sun ◽  
Shuo Zhang ◽  
Hua Zhang ◽  
Yijie Shi
Keyword(s):  
Feature Extraction ◽  
Cost Function ◽  
Network Traffic ◽  
Detection System ◽  
Imbalanced Data ◽  
Detection Performance ◽  
Learning Technology ◽  
The Cost ◽  
Decision Boundaries ◽  
Traffic Detection

Aim. The purpose of this study is how to better detect attack traffic in imbalance datasets. The deep learning technology has played an important role in detecting malicious network traffic in recent years. However, it suffers serious imbalance distribution of data if the traffic model skews towards the modeling in the benign direction, because only a small portion of traffic is malicious, while most network traffic is benign. That is the reason why the authors wrote this manuscript. Methods. We propose a cost-sensitive approach to improve the HTTP traffic detection performance with imbalanced data and also present a character-level abstract feature extraction approach that can provide features with clear decision boundaries in addition. Finally, we design a spark-based HTTP traffic detection system based on these two approaches. Results. The methods proposed in this paper work well in imbalanced datasets. Compared to other methods, the experiment results indicate that our system has F1-score in a high precision. Conclusion. For imbalanced HTTP traffic detection, we confirmed that the method of feature extraction and the cost function is very effective. In the future, we may focus on how to use the cost function to further improve detection performance.

A Practical Botnet Traffic Detection System Using GNN

2022 ◽  
pp. 66-78
Author(s):  
Bonan Zhang ◽  
Jingjin Li ◽  
Chao Chen ◽  
Kyungmi Lee ◽  
Ickjai Lee
Keyword(s):  
Detection System ◽  
Traffic Detection
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