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Jui-Fa Chen, Yu-Ting Liao and Po-Chun Wang
Climate change has exacerbated severe rainfall events, leading to rapid and unpredictable fluctuations in river water levels. This environment necessitates the development of real-time, automated systems for water level detection. Due to degradation, tra...
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Luís P. N. Mendes, Ana M. C. Ricardo, Alexandre J. M. Bernardino and Rui M. L. Ferreira
We present novel velocimetry algorithms based on the hybridization of correlation-based Particle Image Velocimetry (PIV) and a combination of Lucas?Kanade and Liu?Shen optical flow (OpF) methods. An efficient Aparapi/OpenCL implementation of those method...
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Li Wang, Xiaosong Yang and Jianjun Zhang
For video style transfer, naively applying still image techniques to process a video frame-by-frame independently often causes flickering artefacts. Some works adopt optical flow into the design of temporal constraint loss to secure temporal consistency....
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Pavlo Maruschak, Ihor Konovalenko, Yaroslav Osadtsa, Volodymyr Medvid, Oleksandr Shovkun, Denys Baran, Halyna Kozbur and Roman Mykhailyshyn
Modern neural networks have made great strides in recognising objects in images and are widely used in defect detection. However, the output of a neural network strongly depends on both the training dataset and the conditions under which the image was ac...
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Ryota Higashimoto, Soh Yoshida and Mitsuji Muneyasu
This paper addresses the performance degradation of deep neural networks caused by learning with noisy labels. Recent research on this topic has exploited the memorization effect: networks fit data with clean labels during the early stages of learning an...
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