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Laminar-Turbulent Flow Localisation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
0
평가표
1
보존된 평가 기록
1

It is a segmentation task on thermographic measurement images in order to separate laminar and turbulent flow regions on flight body parts.

데이터셋

출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.

Wind Tunnel and Flight Test Experiments

Our dataset comprises $23.468$ non-labelled and $356$ labelled samples where each sample is $512 \times 512 \times 1$ dimensional IR image collected with the thermographic measurement specifications. Some samples contain scars, shadows, salt & pepper noises and contrast burst regions, demonstrating that realistic laminar-turbulent flow observation scenarios are subject to high noise. Besides, a laminar flow area may occur brighter or darker as compared to the regions in a turbulent flow. Due to some effect (e.g. shadowing the sun) it is even possible that, in one part of the image, the laminar flow area appears darker, and in another part, it appears brighter than the turbulent flow area. As you can see in the cover sample: Thermographic measurement examples from wind tunnel and flight test experiments: i. top and bottom row: wind tunnel ii. center row: vertical stabilizer from AFLoNext Project. Note that the red flow-separation lines were semi-automatically drawn as ground-truths by an internal software of our institution. In principle, the software took some pixel samples selected by human experts for each flow region as input, and it accordingly drew laminar flow boundary after statistical analysis on the selected pixels. Finally, if mislocalisation happened in the separation lines, human experts corrected them in an iterative way.

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.