• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.141-147
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• 2021

In this paper, in order to improve the utilization of hyperspectral large-capacity data feature information by reducing complex computations by dimension reduction of neural network inputs in embedded systems, the band selection algorithm is applied in each subset. Among feature extraction and feature selection techniques, the feature selection aim to improve the optimal number of bands suitable for datasets, regardless of wavelength range, and the time and performance, more than others algorithms. Through this experiment, although the time required was reduced by 1/3 to 1/9 times compared to the others band selection technique, meaningful results were improved by more than 4% in terms of performance through the K-neighbor classifier. Although it is difficult to utilize real-time hyperspectral data analysis now, it has confirmed the possibility of improvement.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.356-364
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• 2021

In the formation of a socially oriented economy in the context of European integration, the development of tourism is one of the priority areas that positively affects the socio-economic situation of the country as a whole and its regions in particular, stimulates important economic activities and strengthens Ukraine's positive image in Europe and the world. In view of this, in the framework of a thorough study of the tourism industry it is necessary to assess its potential. This study proposes an assessment of tourism potential in the regional context, which consists of consistent implementation of six steps, namely: first, the definition of research objects for which the tourism potential is determined; secondly, the formation of a set of basic features for assessing tourism potential of certain objects; thirdly, the collection of information on individual indicators, which are selected to assess the tourism potential of the objects; fourth, the calculation of parametric indices by comparing the indicators of each individual object of study (region) with the average values in the set of objects under study; fifth, the definition of a generalized index of tourism potential of the region; sixth, grouping regions by the values of the generalized index of tourism potential. Execution of the stated algorithm involves the use of various methods, in particular, statistical, graphical, parametric, the analysis of hierarchies, matrix and cartographic. Approbation of the proposed assessment of tourism potential at the regional level in Ukraine allowed to group regions according to the values of the generalized index of tourism potential, which can be used as a basis for developing measures to increase and enhance their tourism potential in Ukraine in terms of European integration.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.201-210
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• 2019

This paper proposes the AMCS(Agricultural Machine Control System that distinguishes farms using satellite photos or drone photos of farms and controls the self-driving and operation of farm drones and tractors. The AMCS consists of the LSM(Local Server Module) which separates farm boundaries from sensor data and video image of drones and tractors, reads remote control commands from the main server, and then delivers remote control commands within the management area through the link with drones and tractor sprinklers and the PSM that sets a path for drones and tractors to move from the farm to the farm and to handle work at low cost and high efficiency inside the farm. As a result of AMCS performance analysis proposed in this paper, the PSM showed a performance improvement of about 100% over Dijkstra algorithm when setting the path from external starting point to the farm and a higher working efficiency about 13% than the existing path when setting the path inside the farm. Therefore, the PSM can control tractors and drones more efficiently than conventional methods.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1445-1456
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• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.381-387
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• 2019

The limitations of applying a variety of artificial intelligence to the medical community are, first, subjective views, extensive interpreters and physical fatigue in interpreting the image of an interpreter's illness. And there are questions about how long it takes to collect annotated data sets for each illness and whether to get sufficient training data without compromising the performance of the developed deep learning algorithm. In this paper, when collecting basic images based on acne data sets, the selection criteria and collection procedures are described, and a model is proposed to classify data into small loss rates (5.46%) and high accuracy (96.26%) in the sequential structure. The performance of the proposed model is compared and verified through a comparative experiment with the model provided by Keras. Similar phenomena are expected to be applied to the field of medical and skin care by applying them to the acne classification model proposed in this paper in the future.

• Phonetics and Speech Sciences
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• v.13 no.1
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• pp.73-79
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• 2021

This study investigated the change in lip movement during speech according to aging. For the study, 15 elderly women with an average of 69 years and 15 young women with an average of 22 years were selected. To measure the movement of the lips, the ratio between the minimum point and the maximum point of movement when pronouncing a double vowel was analyzed in pixel units using image analysis software. For clinical utility, the software was produced by applying an automated algorithm and compared with the results of handwork. This study found that the range of the width and length of lips in double vowel tasks was smaller for the elderly than that of the young. A strong positive correlation was found between manual and automated methods, indicating that both methods are useful for extracting lip contours. Based on the above results, it was found that the range of the lips decreased when ignited as aging progressed. Therefore, monitoring the condition of lip performance by simply measuring the movement of lips before aging progresses, and performing exercises to maintain lip range, will prevent pronunciation problems caused by aging.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.4
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• pp.105-118
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• 2006

The purpose of this research is twofold. The first is to develop the measures for evaluating performance of fingerprint sensor modules quantitatively and objectively. The second is to present the methodology for evaluating compatibilities among disparate fingerprint sensors. This paper focuses on the performance evaluation not of fingerprint authentication algorithm but of fingerprint sensors. Presented in this paper are several indicators and their measuring schemes such as the actual resolution of fingerprint images, the level of distortion by horizontal and vertical resolutions of fingerprint image, the intensity distribution for various illuminating conditions. Nine commercial sensor modules have been tested and the test results are expressed by using 95% confidence interval based on 50 acquired fingerprint images. The experimental results are compared with the manufacturer's sensor specification.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.3006-3016
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• 2022

In this study, the images of specific prompt gamma (PG)-rays of 719 keV emitted from proton-boron reactions were analyzed using single-photon emission computed tomography (SPECT). Quantitative evaluation of the images verified the detection of anatomical changes in tumors, one of the important factors in daily adaptive proton therapy (DAPT) and verified the possibility of application of the PG-ray images to DAPT. Six scenarios were considered based on various sizes and locations compared to the reference virtual tumor to observe the anatomical alterations in the virtual tumor. Subsequently, PG-rays SPECT images were acquired using the modified ordered subset expectation-maximization algorithm, and these were evaluated using quantitative analysis methods. The results confirmed that the pixel range and location of the highest value of the normalized pixel in the PG-rays SPECT image profile changed according to the size and location of the virtual tumor. Moreover, the alterations in the virtual tumor size and location in the PG-rays SPECT images were similar to the true size and location alterations set in the phantom. Based on the above results, the tumor anatomical alterations in DAPT could be adequately detected and verified through SPECT imaging using the 719 keV PG-rays acquired during treatment.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1653-1661
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• 2022

In this study, the classification of cold water and normal water based on Geo-Kompsat 2A images was performed. Daily mean surface temperature products provided by the National Meteorological Satellite Center (NMSC) were used, and convolution neural network (CNN) deep learning technique was applied as a classification algorithm. From 2019 to 2022, the cold water occurrence data provided by the National Institute of Fisheries Science (NIFS) were used as the cold water class. As a result of learning, the probability of detection was 82.5% and the false alarm ratio was 54.4%. Through misclassification analysis, it was confirmed that cloud area should be considered and accurate learning data should be considered in the future.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.11
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• pp.305-310
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• 2021

Artificial intelligence technology in the medical field initially focused on analysis and algorithm development, but it is gradually changing to web application development for service as a product. This paper describes a Urinary Stone segmentation model in abdominal CT images and an artificial intelligence web application based on it. To implement this, a model was developed using U-Net, a fully-convolutional network-based model of the end-to-end method proposed for the purpose of image segmentation in the medical imaging field. And for web service development, it was developed based on AWS cloud using a Python-based micro web framework called Flask. Finally, the result predicted by the urolithiasis segmentation model by model serving is shown as the result of performing the AI web application service. We expect that our proposed AI web application service will be utilized for screening test.