Artificial Intelligence
Gaming consoles are very common connected devices which have evolved in functionality and applications (games and beyond) they support. This diversity of traffic generated from these consoles has diverse quality of service (QoS) requirements. However, in order to offer diverse QoS, ISPs and operators must be able to classify this traffic. To enable research in traffic classification (Machine Learning based or other), we have generated and collected this dataset. This is a labelled dataset collected from a gaming console, PlayStation 4.
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This is a Chinese causal knowledge graph with the logic rule form constructed from online financial news.
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The data set contains electrical and mechanical signals from experiments on three-phase induction motors. The experimental tests were carried out for different mechanical loads on the induction motor axis and different severities of broken bar defects in the motor rotor, including data regarding the rotor without defects. Ten repetitions were performed for each experimental condition.
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Including Code & Result of the paper "Unsupervised Paraphrasing via Sentence Reconstruction and Back-translation"
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Our complex street scene(CSS) containing strong light and heavy shadow scenes mainly comes from the Kitti dataset. Our datasets are captured by driving around Karlsruhe's mid-size city, in rural areas, and on highways. We equipped a standard station wagon with two high-resolution color and grayscale video cameras. Up to 15 cars and 30 pedestrians are visible per image. We aim to verify the performance of the algorithm in specific and complex street scenes.
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We propose a driver pattern dataset consists of 51 features extracted from CAN (Controller Area Network) of Hyundai YF Sonata while four drivers drove city roads of Seoul, Republic of Korea. Under the belief that different driving patterns implicitly exist at CAN data, we collected CAN diagnosis data from four drivers in pursuit of research on driver identification, driver profiling, and abnormal driving behavior detection. Four drivers are named A, B, C, and D.
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Recently, the coronavirus pandemic has made the use of facial masks and respirators common, the former to reduce the likelihood of spreading saliva droplets and the latter as Personal Protective Equipment (PPE). As a result, this caused problems for the existing face detection algorithms. For this reason, and for the implementation of other more sophisticated systems, able to recognize the type of facial mask or respirator and to react given this information, we created the Facial Masks and Respirators Database (FMR-DB).
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Robotic Vision
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The CHU Surveillance Violence Dataset (CSVD) is a collection of CCTV footage of violent and non-violent actions aiming to characterize the composition of violent actions into more specific actions. We produced several simple action classes for violent and non-violent actions do add variety and better distribution among simple and complex action classes for RGB and Action Silhouette Videos (enhanced Optical Flow Images) with their localized actions.
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