This database is provided for the Fake News Detection task. In addition to being used in other tasks of detecting fake news, it can be specifically used to detect fake news using the Natural Language Inference (NLI).
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We introduce HUMAN4D, a large and multimodal 4D dataset that contains a variety of human activities simultaneously captured by a professional marker-based MoCap, a volumetric capture and an audio recording system. By capturing 2 female and 2 male professional actors performing various full-body movements and expressions, HUMAN4D provides a diverse set of motions and poses encountered as part of single- and multi-person daily, physical and social activities (jumping, dancing, etc.), along with multi-RGBD (mRGBD), volumetric and audio data. Despite the existence of multi-view color
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This work contains data gathered by a series of sensors (PM 10, PM 2.5, temperature, relative humidity, and pressure) in the city of Turin in the north part of Italy (more precisely, at coordinates 45.041903N, 7.625850E). The data has been collected for a period of 5 months, from October 2018 to February 2019. The scope of the study was to address the calibration of low-cost particulate matter sensors and compare the readings against official measures provided by the Italian environmental agency (ARPA Piemonte).
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This dataset is for light field image augmentaion. The dataset contains 100 pairs of light field image, each of them consists of "original" and "modified". "Original" is light field image with only background, "modified" is light field image with exactly same background and an object on it.
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This dataset includes 24,201,654 tweets related to the US Presidential Election on November 3, 2020, collected between July 1, 2020, and November 11, 2020. The related party name and sentiment scores of tweets, also the words that affect the score were added to the data set.
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The Incheon dataset has been measured from a 24-hour experiment from July 5, 2017 (Starting Time:1438 (HM), to July 6, 2017 (Ending Time: 1458 (HM). The experiment has been carried out over a 2 km distance between the Tx and Rx in the Yellow Sea (Deokjeokdo,Incheon).
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The data set has been consolidated for the task of Human Posture Recognition. The data set consists of four postures namely -
- Sitting,
- Standing,
- Bending and,
- Lying.
There are 1200 images for each of the postures listed above. The images have a dimension of 512 x 512 px.
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In this network, a network US-WGAN, which can generate ultrasonic guided wave signals, is proposed to solve the problem of lack of data sets for ultrasonic nondestructive testing based on deep neural networks. This network was trained on the pre-enhanced data set and US-WGAN-enhanced data set with 3000 epochs, and the ultrasound signals generated by US-WGAN are proved to be of high quality (peak signal to noise ratio score of 30 – 50 dB) and belong to the same distribution population as the original data set.
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This dataset contains nearly 1 Million unique movie reviews from 1150 different IMDb movies spread across 17 IMDb genres - Action, Adventure, Animation, Biography, Comedy, Crime, Drama, Fantasy, History, Horror, Music, Mystery, Romance, Sci-Fi, Sport, Thriller and War. The dataset also contains movie metadata such as date of release of the movie, run length, IMDb rating, movie rating (PG-13, R, etc), number of IMDb raters, and number of reviews per movie.
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This dataset contains 1.65 lakhs tweet ids related to death of Sushant Singh Rajput in English language. For whole dataset with all other fields drop a mail at avishekgarain@gmail.com.
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