Theoretical models and comparison of three focus-error detection methods

1993 ◽  
Author(s):  
Song Shen ◽  
Dongsu Cui ◽  
Xiong Qian ◽  
Yongming Shu
Keyword(s):  
Error Detection ◽  
Theoretical Models ◽  
Detection Methods

scholarly journals Bacterial colonies detecting and counting based on enhanced CNN detection method

2021 ◽  
Vol 233 ◽  
pp. 02012
Author(s):  
Shousheng Liu ◽  
Zhigang Gai ◽  
Xu Chai ◽  
Fengxiang Guo ◽  
Mei Zhang ◽  
...  
Keyword(s):  
Target Detection ◽  
Error Detection ◽  
Detection Rate ◽  
Detection Method ◽  
Difficult Problem ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Detection Model ◽  
Confidence Threshold ◽  
Small Targets

Bacterial colonies detecting and counting is tedious and time-consuming work. Fortunately CNN (convolutional neural network) detection methods are effective for target detection. The bacterial colonies are a kind of small targets, which have been a difficult problem in the field of target detection technology. This paper proposes a small target enhancement detection method based on double CNNs, which can not only improve the detection accuracy, but also maintain the detection speed similar to the general detection model. The detection method uses double CNNs. The first CNN uses SSD_MOBILENET_V1 network with both target positioning and target recognition functions. The candidate targets are screened out with a low confidence threshold, which can ensure no missing detection of small targets. The second CNN obtains candidate target regions according to the first round of detection, intercepts image sub-blocks one by one, uses the MOBILENET_V1 network to filter out targets with a higher confidence threshold, which can ensure good detection of small targets. Through the two-round enhancement detection method has been transplanted to the embedded platform NVIDIA Jetson AGX Xavier, the detection accuracy of small targets is significantly improved, and the target error detection rate and missed detection rate are reduced to less than 1%.

scholarly journals Analysis Of Failure Detection And Visibility Criteria In Pantograph-catenary Interaction

2020 ◽  
pp. 127-135 ◽  
Author(s):  
Sakir Parlakyıldız ◽  
Muhsin Tunay Gencoglu ◽  
Mehmet Sait Cengiz
Keyword(s):  
Fault Detection ◽  
Error Detection ◽  
Failure Detection ◽  
Detection Methods ◽  
Main Subject ◽  
Test Environment ◽  
Railway Systems ◽  
Lighting Conditions ◽  
Rail Systems ◽  
Led Luminaire

The main purpose of new studies investigating pantograph catenary interaction in electric rail systems is to detect malfunctions. In the pantograph catenary interaction studies, cameras with non-contact error detection methods are used extensively in the literature. However, none of these studies analyse lighting conditions that improve visual function for cameras. The main subject of this study is to increase the visibility of cameras used in railway systems. In this context, adequate illuminance of the test environment is one of the most important parameters that affect the failure detection success. With optimal lighting, the rate of fault detection increases. For this purpose, a camera, and a LED luminaire 18 W was placed on a wagon, one of the electric rail system elements. This study considered CIE140–2019 (2nd edition) standards. Thanks to the lighting made, it is easier for cameras to detect faults in the electric trains on the move. As a result, in scientific studies, especially in rail systems, the lighting of mobile test environments, such as pantograph-catenary, should be optimal. In environments where visibility conditions improve, the rate of fault detection increases.

Research on error detection methods for a novel nano-CMM

2010 ◽  
Vol 24 (3) ◽  
pp. 250-256
Author(s):  
Ruixue Xia ◽  
Xiaohuai Chen ◽  
Rongsheng Lu ◽  
Qingping Yu
Keyword(s):  
Error Detection ◽  
Detection Methods

scholarly journals Analysis Of The Effectiveness Of Error Detection In Data Transmission Using Polynomial Code Method

2011 ◽  
Vol 14 (2) ◽  
Author(s):  
Daniel N. Owunwanne
Keyword(s):  
Error Detection ◽  
Data Transmission ◽  
Error Control ◽  
Data Transfer ◽  
Detection Methods ◽  
Error Control Coding ◽  
Transfer Rates ◽  
Free Data ◽  
Ethernet Network ◽  
Corrective Method

Data transmitted from one location to the other has to be transferred reliably. Usually, error control coding algorithm provides the means to protect data from errors. Unfortunately, in many cases the physical link can not guarantee that all bits will be transferred without errors. It is then the responsibility of the error control algorithm to detect those errors and in some cases correct them so that upper layers will receive error free data. The polynomial code, also known as Cyclic Redundancy Code (CRC) is a very powerful and easily implemented technique to obtain data reliability. As data transfer rates and the amount of data stored increase, the need for simple and robust error detection codes should increase as well. Thus, it is important to be sure that the CRCs in use are as effective as possible. Unfortunately, standardized CRC polynomials such as the CRC-32 polynomial used in the Ethernet network standard are known to be grossly suboptimal for important applications, (Koopman, 2002). This research investigates the effectiveness of error detection methods in data transmission used several years ago when we had to do with small amount of data transfer and data storages compared with the huge amount of data we deal with nowadays.  A demonstration of erroneous bits in data frames that may not be detected by the CRC method will be shown. A corrective method to detect errors when dealing with humongous data transmission will also be given.

Error detection methods

1996 ◽  
Vol 28 (3) ◽  
pp. 504-517 ◽  
Author(s):  
Joseph A. Gallian
Keyword(s):  
Error Detection ◽  
Detection Methods

Comparison of two error-detection methods in a mail service pharmacy serving health facilities

2008 ◽  
Vol 48 (3) ◽  
pp. 371-382a ◽  
Author(s):  
Ranjani Varadarajan ◽  
Kenneth N. Barker ◽  
Elizabeth A. Flynn ◽  
Robert E. Thomas
Keyword(s):  
Error Detection ◽  
Health Facilities ◽  
Detection Methods ◽  
Mail Service

High-Integrity GPS/INS Integrated Navigation with Error Detection and Application to LAAS

2011 ◽  
Vol 64 (3) ◽  
pp. 467-493 ◽  
Author(s):  
Fang-Cheng Chan ◽  
Boris Pervan
Keyword(s):  
Kalman Filter ◽  
Fault Detection ◽  
Error Detection ◽  
Measurement Errors ◽  
Local Area ◽  
Detection Methods ◽  
Dynamic State ◽  
Integrated Navigation ◽  
Local Area Augmentation ◽  
Ranging Errors

A dynamic state realization for tightly coupling Global Positioning System (GPS) measurements with an Inertial Navigation System (INS) is described. The realization, based on the direct fusion of GPS and INS systems through Kalman filter state dynamics, explicitly accounts for temporal and spatial decorrelation of GPS measurement errors (such as tropospheric, ionospheric, and multipath errors) through state augmentation, thereby ensuring Kalman filter integrity under fault-free error conditions. Predicted system performance for a Local Area Augmentation System (LAAS) aircraft precision approach application is evaluated using covariance analysis and validated with flight data.Built-in fault detection mechanisms based on the Kalman filter innovations are also evaluated to help provide integrity under certain fault conditions. It is shown that an algorithm based on the integral of Kalman filter innovations outperforms other existing GPS fault detection methods in the detection of slowly developing ranging errors, such as those caused by ionospheric and tropospheric anomalies.

Detecting Atlantic MOC Changes in an Ensemble of Climate Change Simulations

2007 ◽  
Vol 20 (8) ◽  
pp. 1571-1582 ◽  
Author(s):  
S. S. Drijfhout ◽  
W. Hazeleger
Keyword(s):  
Error Detection ◽  
Continuous Monitoring ◽  
Signal To Noise Ratio ◽  
Linear Trend ◽  
Maximum Amplitude ◽  
Internal Variability ◽  
Meridional Overturning Circulation ◽  
Detection Methods ◽  
Signal To Noise ◽  
Ensemble Mean

Abstract Signal-to-noise patterns for the meridional overturning circulation (MOC) have been calculated for an ensemble of greenhouse scenario runs. The greenhouse-forced signal has been defined as the linear trend in ensemble-mean MOC, after year 2000. It consists of an overall decrease and shoaling of the MOC, with maximum amplitudes of 10 Sv (Sv ≡ 106 m3 s−1) per century. In each member the internal variability is defined as the anomaly with respect to the ensemble-mean signal. The interannual variability of the MOC is dominated by a monopole with a maximum amplitude of 2 Sv at 40°N. This variability appears to be driven by the North Atlantic Oscillation (NAO), mainly through NAO-induced variations in the wind field. The signal-to-noise ratio was estimated for various time spans, all starting in 1950 or later. Different noise estimates were made, both with and without intra-annual variability, relevant for episodic and continuous monitoring, respectively, and with and without an estimate of the observational error. Detection of a greenhouse-forced MOC signal on the basis of episodic measurements is impossible before 2055. With continuous monitoring, detection becomes possible after 35 years of observation. The main motivation for calculating signal-to-noise ratios and detection times is their usefulness for local monitoring strategies and detection methods. The two-dimensional pattern of detection times of a MOC change supports the rationale for deploying a sustained monitoring array on at 26°N.

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