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The first bit of light is the gesture of being, on a massive screen of the black panorama. A small point of existence, a gesture of being. The universal appeal of gesture is far beyond the barriers of languages and planets. These are the microtransactions of symbols and patterns which have traces of the common ancestors of many civilizations.
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The advent of the Industrial Internet of Things (IIoT) has led to the availability of huge amounts of data, that can be used to train advanced Machine Learning algorithms to perform tasks such as Anomaly Detection, Fault Classification and Predictive Maintenance. Most of them are already capable of logging warnings and alarms occurring during operation. Turning this data, which is easy to collect, into meaningful information about the health state of machinery can have a disruptive impact on the improvement of efficiency and up-time. The provided dataset consists of a sequence of alarms logged by packaging equipment in an industrial environment. The collection includes data logged by 20 machines, deployed in different plants around the world, from 2019-02-21 to 2020-06-17. There are 154 distinct alarm codes, whose distribution is highly unbalanced.
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The Badminton Activity Recognition (BAR) Dataset was collected for the sport of Badminton for 12 commonly played strokes. Besides the strokes, the objective of the dataset is to capture the associated leg movements.
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This is the dataset associated with the IEEE-JBHI submission "Synthesizing Electrocardiograms With Atrial Fibrillation Characteristics Using Generative Adversarial Networks". This dataset contains 4,768 synthesized atrial fibrillation (AF)-like ECG signals stored in PhysioNet MAT/HEA format.
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There are 84168 blogs in the dataset.
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A total of 10,003 images of product design submissions of Hardware Product Design Competitionwere collected to form the product design image database, which has 835 samples of awarded class (high aesthetic level), 4,990 samples of qualified class (middle aesthetic level) and 4,178 samples of eliminated class (low aesthetic level). The Product Design Aesthetic Database includes dataset of image features extracted by the optimal method VGG-19.
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Real-World Multimodal Foodlog Database (RWMF) database is built for evaluating the multimodal retrieval algorithm in real-life dietary environment, and it has 7500 multimodal pairs in total， where each image can be related to multiple texts and each text can be related to multiple images. Details of this database can be found in this paper: Pengfei Zhou, Cong Bai, Kaining Ying, Jie Xia, Lixin Huang, RWMF: Real-World Multimodal Foodlog Database, ICPR 2020
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Three month Coffee Leaf Rust dataset generated by the Cyber Physical Data Collection System.
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This dataset concludes source data which is professional fact descriptions from Chinese law office website and target data which is non-professional fact descriptions from daily spoken language.
The dataset is for transfer learning in law domain.
The dataset also concludes processed dictionary and .npy files.
The task of transfer learning is to predict the accusation based on the description.
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