• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.292-302
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• 2020

Machine learning algorithms have made immense contributions in various fields including sonar and radar applications. Recently developed Cycle-Consistency Generative Adversarial Network (CycleGAN), a variant of GAN has been successfully used for unpaired image-to-image translation. We present a modified CycleGAN for translation of underwater ship engine sounds with high perceptual quality. The proposed network is composed of an improved generator model trained to translate underwater audio from one vessel type to other, an improved discriminator to identify the data as real or fake and a modified cycle-consistency loss function. The quantitative and qualitative analysis of the proposed CycleGAN are performed on publicly available underwater dataset ShipsEar by evaluating and comparing Mel-cepstral distortion, pitch contour matching, nearest neighbor comparison and mean opinion score with existing algorithms. The analysis results of the proposed network demonstrate the effectiveness of the proposed network.

• Journal of the Korean Society for Marine Environment & Energy
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• v.12 no.3
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• pp.181-187
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• 2009

To estimate the status and volume of artificial reefs(ARs) deployed at the sea bottom in fishing grounds, this study assessed the initial volume of ARs, the cubic volume of AR groups, and the porosity of each AR using image data collected during a survey using a multi-beam echo sounder(MBES) and a side scan sonar(SSS). These results were compared with data collected during diver surveys and used to develop a new method and prediction formulas for countermeasures, facility volume, and efficient use of volume for deployed ARs(cubic concrete). The field survey results for nine ARs deployed in the Busan Sea region were calculated, and the average value of coefficient k(indicating the efficient use of volume ratio) among ARs was 0.753, and the correlation between coefficient k and year(Yr) of deployment was calculated as k=0.0023Yr+0.725. The relationship between these two factors was poor. In years following the deployment of artificial reefs, coefficient k and year of deployment were not correlated, in spite of the hardening ground due to subsidence and the reduced distance between ARs. Consequently, it is reasonable to suppose that coefficient k was defined by bottom surface conditions and initial deployment conditions.

• Tunnel and Underground Space
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• v.28 no.5
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• pp.387-399
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• 2018

Mine reclamation project is closely related to human's past mining activities and the current human's living environment. It is a reason for the national management. In order to efficiently carry out mine reclamation projects, a precise investigation and analysis of the underground space of the abandoned mine is required. Korea MINE RECLAMATION Corp. is developing a practical technology that is effective in investigating and actually measuring underground cavities. MIRECO EYE system is an exploration equipment for 3D digitization and figuration of underground cavities. As combining a laser, sonar and image acquisition technology, it enables access to information about inaccessible underground cavities and effective management of subsidence risk of mined area. and currently it is also utilized for various purposes in related areas such as investigating urban sinkholes. This article is precise numerical and geometric information analysis obtained through MIRECO EYE system.

• 한국해양학회지
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• v.29 no.3
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• pp.239-247
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• 1994

Bedform morphology of the giant ripples have been studied on the continental shelf of the Yellow Sea, East China sea and Korea-Tsushima Strait on the basis of side-scan sonar image, sub-bottom profile, sedimentary facies, geomorphology evidence and hydrology. There are well developed giant ripples ranging from 100 to 500 m in wavelengths and from 2 to 10 m in wave height at nine sites in the study area, which are covered by medium to fine sand. Most of them have been formed under the present hydrologic regime where the tidal currents and local currents or turbulence flows are superimposed. In the study area, giant ripples are produced on two different environments. One is at the geomorphic narrow zone such as the Korea Strait where currents are accelerated by the topographic effects, while the other is the sandy flat plain where tidal currents and local currents are harmonized.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.181-190
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• 2014

The underwater acoustic lens system is one of the systems getting high-resolution images on the seafloor by the beam forming method using acoustic lens. The beam forming using acoustic lenses reduces complexity and driving power. When receiving an incoming beam with the acoustic lens array, beam pattern analysis and arrangement problem of the array sensor must be addressed. Introducing SIR (Signal to Interference Ratio), the relationship among sensor interval, beam pattern and image quality would be analyzed. Generally if the sensor interval getting wider, the less effect of the side lobes makes SIR high. If the amplitude of a side lobe is high, SIR is generally getting low. The type of the apodization function changes the width, shape and amplitude of both main lobe and side lobes. Thus an appropriate apodization function can improve SIR. In this paper, SIR is stable at the sensor interval of 13mm with 0-10dB, which is not high relatively. By applying the Chebyshev function, the SIR becomes 80dB over the sensor interval of 37 mm or higher. The Hann and triangular functions demonstrate better SIR when the sensor interval becomes narrower.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.117-126
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• 2020

A maritime object detection system is an intelligent assistance system to maritime autonomous surface ship(MASS). It detects automatically floating debris, which has a clash risk with objects in the surrounding water and used to be checked by a captain with a naked eye, at a similar level of accuracy to the human check method. It is used to detect objects around a ship. In the past, they were detected with information gathered from radars or sonar devices. With the development of artificial intelligence technology, intelligent CCTV installed in a ship are used to detect various types of floating debris on the course of sailing. If the speed of processing video data slows down due to the various requirements and complexity of MASS, however, there is no guarantee for safety as well as smooth service support. Trying to solve this issue, this study conducted research on the minimization of computation volumes for video data and the increased speed of data processing to detect maritime objects. Unlike previous studies that used the Hough transform algorithm to find the horizon and secure the areas of interest for the concerned objects, the present study proposed a new method of optimizing a binarization algorithm and finding areas whose locations were similar to actual objects in order to improve the speed. A maritime object detection system was materialized based on deep learning CNN to demonstrate the usefulness of the proposed method and assess the performance of the algorithm. The proposed algorithm performed at a speed that was 4 times faster than the old method while keeping the detection accuracy of the old method.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1643-1652
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• 2022

Deposited Marine Debris(DMD) can negatively affect marine ecosystems, fishery resources, and maritime safety and is mainly detected by sonar sensors, lifting frames, and divers. Considering the limitation of cost and time, recent efforts are being made by integrating underwater images and artificial intelligence (AI). We conducted a comparative study of You Only Look Once Version 5 (YOLOv5) and You Only Look Once Version 7 (YOLOv7) models to detect DMD from underwater images for more accurate and efficient management of DMD. For the detection of the DMD objects such as glass, metal, fish traps, tires, wood, and plastic, the two models showed a performance of over 0.85 in terms of Mean Average Precision (mAP@0.5). A more objective evaluation and an improvement of the models are expected with the construction of an extensive image database.

• Economic and Environmental Geology
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• v.49 no.5
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• pp.381-388
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• 2016

The purpose of this study is to integrate and visualize using mapping techniques based on precise seabed geomorphology, seafloor backscattering images and high-resolution underwater images of the nearshore area around the Dokdo, in the East Sea. We have been obtained the precise topography map using multibeam echosounder system around the nearshore area(~50 m) of the southern part of the Seodo. Side scan sonar survey for analysis seafloor backscattering images was carried out in the same area of topography data. High-resolution underwater images(zone(a), zone(b), zone(c)) were taken in significant habitat scope of the nearshore area of the southern part of the Seodo. Using the results of bathymetry, seafloor backscattering images, high-resolution underwater images, we performed an integrated visualization about the nearshore area of the Dokdo. The integrated visualizing techniques are possible to make the seabed characteristic mapping results of the nearshore area of the Dokdo. The integrated visualization results present more complex and reliable information than separate geological products for seabed environmental mapping study and it is useful to understand the relation between seafloor characteristics and topographic environments of the study area. The integrated visualizing techniques and mapping analysis need to study sustainably and periodically, for effective monitoring of the nearshore ecosystem of the Dokdo.