Image Processing
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The dataset is genrated by the fusion of three publicly available datasets: COVID-19 cxr image (https://github.com/ieee8023/covid-chestxray-dataset), Radiological Society of North America (RSNA) (https://www.kaggle.com/c/rsna-pneumonia-detection-challenge), and U.S. national library of medicine (USNLM) collected Montgomery country - NLM(MC) (http
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The current maturity of autonomous underwater vehicles (AUVs) has made their deployment practical and cost-effective, such that many scientific, industrial and military applications now include AUV operations. However, the logistical difficulties and high costs of operating at-sea are still critical limiting factors in further technology development, the benchmarking of new techniques and the reproducibility of research results. To overcome this problem, we present a freely available dataset suitable to test control, navigation, sensor processing algorithms and others tasks.
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Results(including reported and extra results) for LSstab. Please refer to our paper "Efficient real-time video stabilization with a novel least squares formulation and parallel AC-RANSAC".
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This dataset is flotation froth sequence images, a total of 2386 folders, that is, 2386 groups of froth sequence images. The data comes from a mine in southern China, and the digital camera collected the froth videos every 5 minutes during the period from 2019.08.01 to 2019.12.01. Each group of froth sequence images contains 12 consecutive frames and the sampling time is 0.4s. This dataset is suitable for image processing, pattern recognition, and artificial intelligence.
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Deep learning undoubtedly has had a huge impact on the computer vision community in recent years. In light field imaging, machine learning-based applications have significantly outperformed their conventional counterparts. Furthermore, multi- and hyperspectral light fields have shown promising results in light field-related applications such as disparity or shape estimation. Yet, a multispectral light field data\-set, enabling data-driven approaches, is missing. Therefore, we propose a new synthetic multispectral light field dataset with depth and disparity ground truth.
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