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왕복동식 수소압축기의 스너버 내부 맥동압력에 관한 수치해석
심규진(KyuJin Shim),이중섭(ChungSeub Yi),악바르완다알리(Wanda Ali Akbar),정한식(HanShik Chung),정효민(HyoMin Jeong),김무근(MooGeun Kim) 대한기계학회 2006 대한기계학회 춘추학술대회 Vol.2006 No.6
Nowadays, study about hydrogen fuel which consist of hydrogen extraction and reform ing processes, fuel cell equipment, and receptacle are flourishing all over the world. Currently, Korea hydrogen station is still underdeveloping. And also the most important part which is hydrogen compressor has not been developed. Snubber is one of the important parts in hydrogen compressing system. It is installed before and after reciprocating hydrogen compressor. Snubber has two functions. One is making down pulsation waveform. Because pressure hydrogen gas where is after passing through reciprocation compressor part has high pulsation waveform, so this waveform has to decline. And the other function is precipitating alien substances to outside. Normally, even if 99.99% hydrogen gas is still containing alien substance. Buffer is set up inside snubber and the waveform will hit buffer. This snubber study uses CFD analysis, then it compares between with-buffer snubber and without-buffer snubber.
다중 물체 추적을 위한 의사 깊이 기반 특징 벡터 갱신 알고리즘
심규진(Kyujin Shim),고강욱(Kangwook Ko),황주비(Jubi Hwang),김창익(Changick Kim) 대한전자공학회 2023 대한전자공학회 학술대회 Vol.2023 No.11
Multi-Object Tracking (MOT) is an essential task in computer vision, applied various fields like video surveillance and autonomous driving. Recently, tracking-by-detection-based trackers have shown promising performance and have become predominant approaches in MOT. Our study presents a novel pseudo-depth-based appearance feature vector update algorithm to improve those tracking-by-detection-based multi-object trackers. Experiments on the DanceTrack dataset reveal significant performance improvements compared to the previous feature updating strategies.
부분적인 스크린 영상 혼합을 통한 합성곱 신경망의 영상 인식 성능 향상
변준영(Junyoung Byun),심규진(Kyujin Shim),김창익(Changick Kim) 대한전자공학회 2019 대한전자공학회 학술대회 Vol.2019 No.11
Data augmentation is a way of improving the generalization ability of deep neural networks by expanding their training data with pre-defined transformations. For image recognition tasks, traditional data augmentation methods transform an image by using simple techniques such as random horizontal flipping and cropping. However, several recent methods have been proposed to augment training data by linearly interpolating two images with arbitrary proportions. Although they can further improve the generalization ability, they use a randomly chosen mixing ratio throughout a pair of images, which may ignore their local characteristics. In this paper, we propose a novel data augmentation method that can vary the mixing ratio according to the local brightness. Our method partially blends two images with Screen blend mode. We have also shown that CNNs can be successfully trained, only with the blended inputs. Experimental results on the CIFAR-10 and CIFAR-100 datasets have shown that the proposed method yields superior performance than existing methods.
이경환(KyeongHwan Lee),심규진(KyuJin Shim),악바르 완다 알리(Wanda Ali Akbar),정한식(HanShik Chung),정효민(HyoMin Jeong) 대한기계학회 2006 대한기계학회 춘추학술대회 Vol.2006 No.11
Nowadays, study about hydrogen fuel which consist of hydrogen extraction and reforming processes, fuel cell equipment, and receptacle are flourishing allover the world. Currently, Korea hydrogen station is still underdeveloping. And also the most important part which is hydrogen compressor has not been developed. Snubber is one of the important parts in hydrogen compressing system. It is installed before and after reciprocating hydrogen compressor. Snubber has two functions. One is making down pulsation waveform. Because pressure hydrogen gas where is after passing through reciprocation compressor part has high pulsation waveform, so this waveform has to decline. And the other function is precipitating alien substances to outside. Normally, even if 99.99% hydrogen gas is still containing alien substance. Buffer is set up inside snubber and the waveform will hit buffer. This snubber study uses CFD.
고강욱(Kangwook Ko),김희선(Hee-seon Kim),심규진(Kyujin Shim),황주비(Jubi Hwang),김창익(Changick Kim) 대한전자공학회 2023 대한전자공학회 학술대회 Vol.2023 No.11
This paper addresses the critical problem of Multiple Object Tracking (MOT) in computer vision. While traditional methods have primarily focused on pedestrian tracking, recent advances in the Transformer-based DETR (DEtection TRansformer) architecture, applied to object detection, have opened new possibilities for MOT. We introduce an approach that incorporates temporal characteristics into object tracking, utilizing moving averages in the Transformers encoder for image feature maps and decoder for tracking queries. Our method demonstrates improved performance, particularly in query mix, on the challenging DanceTrack dataset. By enhancing MOTRv2 with these temporal features, we pave the way for more effective and robust multiple object tracking solutions.