• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.3
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• pp.215-222
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• 2022

Artificial neuromorphic devices are considered the key component in realizing energy-efficient and brain-inspired computing systems. For the artificial neuromorphic devices, various material candidates and device architectures have been reported, including two-dimensional materials, metal-oxide semiconductors, organic semiconductors, and halide perovskite materials. In addition to conventional electrical neuromorphic devices, optoelectronic neuromorphic devices, which operate under a light stimulus, have received significant interest due to their potential advantages such as low power consumption, parallel processing, and high bandwidth. This article reviews the recent progress in optoelectronic neuromorphic devices using various active materials such as two-dimensional materials, metal-oxide semiconductors, organic semiconductors, and halide perovskites

• Journal of Korea Multimedia Society
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• v.25 no.5
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• pp.676-684
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• 2022

As realistic media are widespread in various image processing areas, image or video compression is one of the key technologies to enable real-time applications with limited network bandwidth. Generally, image or video compression cause the unnecessary compression artifacts, such as blocking artifacts and ringing effects. In this study, we propose a Deep Residual Channel-attention Network, so called DRCAN, which consists of an input layer, a feature extractor and an output layer. Experimental results showed that the proposed DRCAN can reduced the total memory size and the inference time by as low as 47% and 59%, respectively. In addition, DRCAN can achieve a better peak signal-to-noise ratio and structural similarity index measure for compressed images compared to the previous methods.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.226-233
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• 2022

Video surveillance is widely used in security surveillance, military navigation, intelligent transportation, etc. Its main research fields are pattern recognition, computer vision and artificial intelligence. This article uses OpenCV to detect and track vehicles, and monitors by establishing an adaptive model on a stationary background. Compared with traditional vehicle detection, it not only has the advantages of low price, convenient installation and maintenance, and wide monitoring range, but also can be used on the road. The intelligent analysis and processing of the scene image using CAMSHIFT tracking algorithm can collect all kinds of traffic flow parameters (including the number of vehicles in a period of time) and the specific position of vehicles at the same time, so as to solve the vehicle offset. It is reliable in operation and has high practical value.

• Current Optics and Photonics
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• v.6 no.5
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• pp.463-472
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• 2022

At certain wavelengths, single-pixel imaging is considered to be a solution that can achieve high quality imaging and also reduce costs. However, achieving imaging of complex scenes is an overhead-intensive process for single-pixel imaging systems, so low efficiency and high consumption are the biggest obstacles to their practical application. Improving efficiency to reduce overhead is the solution to this problem. Salient object detection is usually used as a pre-processing step in computer vision tasks, mimicking human functions in complex natural scenes, to reduce overhead and improve efficiency by focusing on regions with a large amount of information. Therefore, in this paper, we explore the implementation of salient object detection based on single-pixel imaging after a single pixel, and propose a scheme to reconstruct images based on Fourier bases and use U²Net models for salient object detection.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.389-394
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• 2023

Based on intelligent visual information and 5G, this paper studies the intelligent visual communication of landscape bamboo buildings, and provides a new method of intelligent perception and interactive computing for the real world, which can represent, model, Perception and cognition; through the integration of virtual and real, the situational understanding of the human-machine-material fusion environment and the interaction with nature. The 5G network can well meet the combination of high-bandwidth uplink transmission and low-latency downlink control. At the same time, 5G-based AR intelligent inspection, remote operation and maintenance guidance, and machine vision inspection. Taking the bamboo building as an example, through field inspections to analyze tourism Bamboo buildings before and after development, and the intelligentization of bamboo buildings based on 5G and visual modeling.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1470-1473
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• 2011

밀집한 작은 대상으로 구성된 웹과 응용프로그램을 사용할 때, 저 시력인은 원하는 대상을 선택하기 어렵다. 이로 인해 필요로 하는 정보의 접근이 차단되어 사회구성원으로서의 역할을 수행하는 것이 제한된다. 저 시력인을 위한 커서 인터페이스는 대상을 확대하고, 색상을 변화시켜 인식률을 높인다. 그리고 대상 사이의 충분한 거리를 확보하고, 대상의 정보를 음성으로 제공하여 원하지 않는 대상의 선택을 방지한다. 일반적인 환경과 지시확대기의 인터페이스 환경을 제안한 커서 인터페이스와 실험을 통해서 비교하였다. 실험결과에서 제안한 커서 인터페이스가 대상을 선택하는데, 가장 적은 시간이 걸렸다. 제안한 커서 인터페이스를 사용하면, 저 시력인이 웹과 응용프로그램을 쉽게 사용하여 정보의 접근성이 향상된다.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.794-802
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• 2022

The recovery of reasonable depth information from different scenes is a popular topic in the field of computer vision. For generating depth maps with better details, we present an efficacious monocular depth prediction framework with coordinate attention and feature fusion. Specifically, the proposed framework contains attention, multi-scale and feature fusion modules. The attention module improves features based on coordinate attention to enhance the predicted effect, whereas the multi-scale module integrates useful low- and high-level contextual features with higher resolution. Moreover, we developed a feature fusion module to combine the heterogeneous features to generate high-quality depth outputs. We also designed a hybrid loss function that measures prediction errors from the perspective of depth and scale-invariant gradients, which contribute to preserving rich details. We conducted the experiments on public RGBD datasets, and the evaluation results show that the proposed scheme can considerably enhance the accuracy of depth prediction, achieving 0.051 for log10 and 0.992 for δ<1.25³ on the NYUv2 dataset.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.1029-1030
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• 2023

시각장애인의 독립보행은 많은 위험 부담과 어려움을 안고 있다. 본 연구는 이러한 어려움을 해결하고자 사용자에게 GPS를 통해 목적지까지 안전한 경로로 안내하는 기능을 제공한다. 사물 인식 알고리즘을 통해 주행 시 필요한 장애물 판별과 신호등의 색상 등을 인식한다. 그리고 아두이노 초음파 센서를 활용하여 장애물과 사용자 간의 거리를 인식하고, 블루투스 모듈을 통해 측정한 값을 송신하여 구간별에 따라 사용자에게 경고음을 울린다. 더 나아가 AR 기능을 통해서 장애물을 입체적으로 강조하여 표시함으로써 저시력 장애인들이 장애물과 충돌하는 것을 예방한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.1035-1036
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• 2023

본 논문은 저시력자를 위한 체외진단 의료기기 결과 판독 시스템을 제안한다. 이 시스템은 YOLOv8n 객체 탐지 모델을 기반으로 하며, 라즈베리파이4B+에서 홈 디바이스 형태로 구현하였다. 사용자는 음성 및 물리 버튼을 통해 명령을 입력하고, 동작 감지를 통해 자동으로 체외진단 의료기기를 촬영하여 학습된 모델로 결과를 판독하고 해당 결과를 사용자에게 출력한다. 또한, 판독 결과물과 함께 검사 일시 및 의료기기 종류를 데이터베이스에 저장하여 사용자에게 보다 높은 편의성을 제공한다.

• Archives of Craniofacial Surgery
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• v.25 no.1
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• pp.48-50
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• 2024

Identifying tumors or wounds on the scalp is difficult because hair blocks the vision during surgery and suturing. In the meantime, we have commonly used hairpins to hold the hair for a clearer view; however, we would like to suggest a new method, a "hair-fixing sheet," consisting of hook-like surface. We applied the two methods, hair-fixing sheets and hairpins, assuming several situations. In these situations, it was possible to fix a wider range or various shapes more conveniently using a hair-fixing sheet than using several hairpins at a similarly low cost. In addition, it was easy to change the hair to be fixed, remove it postoperatively, and prevent the hair from being pulled out, thereby preventing additional postoperative pain.