Determination of 3-D weld seams in ship blocks using a laser vision sensor and a neural network

Yoo, Wan-Suk; Na, S.-J.

doi:10.1016/s0278-6125(03)80049-3

Cited by 15 publications

(7 citation statements)

References 5 publications

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“…There is also a lot of information that can be obtained using sensors, and many of the security systems are based on cameras or laser vision . Machine vision sensors are a common approach to monitor environments .…”

Section: Related Workmentioning

confidence: 99%

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Real‐time force doors detection system using distributed sensors and neural networks

et al. 2019

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Intelligent security systems have evolved enormously in the last few years. Most of these security systems use a group of physics sensors and algorithms for data analysis and communication systems to notify security alarms. Many security systems that are included in doors can detect intruders when they have already opened the door, but not while intruders are forcing upon the door. However, some security systems include preventive systems, which can detect intruders before they open the door. These preventive systems are usually based on video cameras (image processing) or in‐presence sensors, which can generate many false positives, for instance, when a person is next to the door for a few seconds, even if this person is not manipulating the door. This research work proposes a novel force door detection system. The system includes a specific device for monitoring door small vibrations and movements; it analyzes these data using neural networks to detect accurately if someone is forcing upon the door. Artificial intelligence must be able to categorize data records without confusing when someone is forcing upon the door with other actions, like knocking on the door.

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Section: Related Workmentioning

confidence: 99%

“…26,27 There is also a lot of information that can be obtained using sensors, and many of the security systems are based on cameras or laser vision. 28 Machine vision sensors are a common approach to monitor environments. 29 There is also some controversy about protection and privacy when security systems take photos or record videos.…”

Section: Related Workmentioning

confidence: 99%

Real‐time force doors detection system using distributed sensors and neural networks

et al. 2019

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“…Mostafa et al [20] worked on an automatic target recognition system based on three-dimensional reconstruction of the target from an image sequence. Yoo et al [21] studied an automatic welding of the 3D seam. In their paper, a neural network with 2-D image data was developed and tested in order to get the pattern type.…”

Section: Literature Reviewmentioning

confidence: 99%

Automatic target recognition on land using three dimensional (3D) laser radar and artificial neural networks

Goztepe¹

2013

sajie

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During combat, measuring the dimensions of targets is extremely important for knowing when to fire on the enemy. The importance of identifying a known target on land emphasizes the importance of techniques devoted to automatic target recognition. Although a number of object-recognition techniques have been developed in the past, none of them have provided the desired specifics for unidentified target recognition. Studies on target recognition are largely based on images that assume that images of a known target can be readily viewed under any circumstance. But this is not true for military operations conducted on various terrains under specific circumstances. Usually it is not possible to capture images of unidentified objects because of weather, inadequate equipment, or concealment. In this study, a new approach that integrates neural networks and laser radar has been developed for automatic target recognition in order to reduce the abovementioned problems. Unlike current studies, the proposed model uses the geometric dimensions of unidentified targets in order to detect and recognise them under severe weather conditions. OPSOMMINGDie bepaling van teikenafmetings is van besondere belanggedurende gevegte sodat vuurtydstipte sodoende vasgelê kan word. In hierdie opsig word outomatiese uitkenning van teikentipe dus ook belangrik. Laasgenoemde tegnieke het desnieteenstaande nie besonder presteer met die uitkenning van vreemdeteikentipes nie. Terreintoestande, weersomstandighede, swak waarnemingstoerusting en kamoeflering speel in die verband ook 'n rol. Nuwerwetse toerusting wat gebruikmaak van neurale netwerke laserradar word voorgehou as 'n oplossing vir die vraagstuk onder uiteenlopende omgewingstoestande.

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“…Monitors quality of principal components used in auto body assembly (Jang and Yang. 2001) Estimates unit manufacturing cost of a new type of auto disk brakes (Cavalieri et al 2004) Identifies 3D weld seams in ship blocks during hull assembly process (Yoo and Na. 2003) Transportation…”

Section: Manufacturingmentioning

confidence: 99%

Using artificial neural networks for transport decisions: Managerial guidelines

Cook

Jenicke

Gibson

2010

JOTM

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One information technology that may be considered by transportation managers, and which is included in the portfolio of technologies that encompass TMS. is artificial neural networks (ANNs). These artificially intelligent computer decision support software provide solutions by finding and recognizing complex patterns in data. ANNs have been used successfully by transportation managers to forecast transportation demand, estimate future transport costs, schedule vehicles and shipments, route vehicles and classify earners for selection. Artificial neural networks excel in transportation decision environments that are dynamic, complex and unstructured. This article introduces ANNs to transport managers by describing ANN technological capabilities, reporting the current status of transportation neural network applications, presenting ANN applications that offer significant potential for future development and offering managerial guidelines for ANN development.

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Determination of 3-D weld seams in ship blocks using a laser vision sensor and a neural network

Cited by 15 publications

References 5 publications

Real‐time force doors detection system using distributed sensors and neural networks

Real‐time force doors detection system using distributed sensors and neural networks

Automatic target recognition on land using three dimensional (3D) laser radar and artificial neural networks

Using artificial neural networks for transport decisions: Managerial guidelines

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