Artificial Intelligence
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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A team of researchers from Qatar University, Doha, Qatar, and the University of Dhaka, Bangladesh along with their collaborators from Malaysia in collaboration with medical doctors from Hamad Medical Corporation and Bangladesh have created a database of chest X-ray images for Tuberculosis (TB) positive cases along with Normal images. In our current release, there are 3500 TB images, and 3500 normal images.
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This is the five mainstream stock market indices dataset. It includes XJO, DJI, IXIC, HSI, and N225 indices from Sep. 2010 ~ Aug. 2020.
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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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This is a dataset of diabetic foot. We are preparing to publish this dataset.
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This is for BGP anomaly analysis
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This dataset contains facial expressions from different sides. the top-level videos are shot on Logitech c270 and the bottom ones are shot with an LG g6. The videos are continuous shots at 480p from different angles.
This is meant to serve as a dataset for facial expression recognition under different angles and poses.
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ALL-IDB (Acute Lymphoblastic Leukemia) Image Database for Image Processing
ALL-IDB dataset comprises of two subsets among them one subset has 260 segmented lymphocytes of them 130 belongs to the leukaemia and the remaining 130 belongs to the non leukaemuia class it requires only classification. second subset has around 108 non segmented blood images that belongs to the leukaemia and non leukaemia groups thus requires segmentation and classification.
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A speech dataset used for fake speech detection. The fake speech are generated by 8 well-known latest deep learning based open-sourced tools and 8 commercial speech synthesis products. All speech are in Chinese or English. It contains more than 127,890 synthetic speech and 14,400 natural speech in English and mandarin Chinese languages.
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