• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.29-35
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• 2021

License plate recognition plays a key role in intelligent transportation systems. Therefore, it is a very important process to efficiently detect the number and character areas. In this paper, we propose a method to effectively detect license plate number area by applying deep learning and semantic image segmentation algorithm. The proposed method is an algorithm that detects number and text areas directly from the license plate without preprocessing such as pixel projection. The license plate image was acquired from a fixed camera installed on the road, and was used in various real situations taking into account both weather and lighting changes. The input images was normalized to reduce the color change, and the deep learning neural networks used in the experiment were Vgg16, Vgg19, ResNet18, and ResNet50. To examine the performance of the proposed method, we experimented with 500 license plate images. 300 sheets were used for learning and 200 sheets were used for testing. As a result of computer simulation, it was the best when using ResNet50, and 95.77% accuracy was obtained.

• The Journal of Fisheries Business Administration
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• v.33 no.1
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• pp.69-85
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• 2002

Reduction of fishing grounds, which was caused by the recent fisheries agreements between Korea, Japan, and China, Is Increasing the important of coastal fisheries. Korea's coastal fisheries, however, need special management measures owing to the following problems. First, there are too many fishing fleets even though fisheries resources are continuously decreasing. Despite the fact that some of the fishing vessels have been scrapped, there still remain too many vessels and especially approximately 27,000 vessels increased during 1997-1998. Second, as the condition of fisheries resources changed radically, many fishermen are fishing by methods which they were not permitted to. These fishing methods cannot be legally supported and so there is a huge gap between the system and the reality, Third, two or three licenses are given to each coastal fishing vessel because a single license cannot give sufficient income, but some of these are formally acquired. So under such circumstances, efficient management of fisheries is impossible. Fourth, absence of demarcation among regions and industries is causing frequent conflicts and there are concerns about the decreasing fisheries resources due to competitive fishing practices. Therefore, considering the above mentioned problems Korea's coastal fisheries management should be developed as the following: First, new licenses should be limited while expanding the buy-back program. The government is currently planning to limit new licenses by introducing the fixed license number system in coastal fisheries but is somewhat passive about the buy-back program. Second, fisheries management which is based on self-regulation should be established. In order to increase the effect of fisheries management, the fishermen should decide by themselves the fish and fishing methods they would be exploiting and directly regulate them. Third, it is necessary to integrate the licenses of coastal fisheries. Since coastal fisheries management through the license system has distinct limitations, it is preferable to unify risking licenses and let the fishermen decide specific matters on their own. Finally, it is necessary to establish boundaries among the regions and industries. Joint fishing areas among regions(cities and provinces) should be established and fishing in other areas should be permitted on condition of paying the required fees. On the other hand, it is also necessary to permit coastal fishing only within certain distances.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.284-286
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• 2009

In this paper, we consider a cognitive radio system operating as secondary user. It uses an empty channel that is not currently used by primary users having the license to the channel. In the previous works, secondary user looks for an empty channel by choosing any channel in order or randomly and by sensing the channel to distinguish whether primary users are using. But if primary user is fixed type, we will find an empty channel faster than the mentioned channel selecting methods by using a method considering prior information about cases that primary user used the channel, since it is possible to analogize the channel access possibility of primary user according to regular time and position. Therefore, we propose a channel searching method based on the channel list for the purpose of reducing the channel searching time and improving throughput of secondary users. Firstly, we determine a weighting value of each channel based on the history of channel activities of primary users. This value is added to current channel state buffer and we search an empty channel from channel with smallest value to one with the biggest value. Finally, we compare the performances of the proposed method with those of the sequential channel searching and the random channel searching methods in terms of the average channel searching time and the average number of transmissions of secondary user.