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We introduced the task of acoustic question answering (AQA) in https://arxiv.org/abs/1811.10561.
A second version of the dataset was introduced in https://arxiv.org/abs/2106.06147
This dataset aim to promote research in the acoustic reasoning area.
It comprise Acoustic Scenes and multiple questions/answers for each of them.
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This dataset accompanies the IEEE Journal of Oceanic Engineering Special Issue on Verification and Validation of Airgun Source Signature and Sound Propagation Models. The special issue has is its origins in the International Airgun Modelling Workshop (IAMW) held in Dublin, Ireland, on 16 July 2016 (Ainslie et al., 2016).
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The performance of most of the classification models is dependent on the data used for training. The data must be reliable, robust and meticulously labelled. In order to form such a data a systematical approach has been designed and moreover, it should be. The data set was collected from a well-known source, namely Center for Language Engineering available at http://www.cle.org.pk.
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A solenoid-operated valve with DC resistance of about 10.3 Ω was exposed to 50 % RH, its rated temperature of 80 °C, and powered at its rated voltage of 12 VDC. (Note: the valve was unrated with regards to relative humidity, RH.) Using Fourier transform infrared (FTIR) spectroscopy, the insulation material was found to be a combination of polystyrene and polyethylene terephthalate. The wire gauge was not disclosed in the valve information sheet.
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Occlusion, glare and secondary reflections formed due to and on the spectacles - results in poor detection, localization, and recognition of eye/face features. We term all the problems related to the usage of spectacles as The spectacle problem. Though several studies on the spectacle detection and removal have been reported in the literature, the study focusing on spectacle problem removal is very limited. One of the main reasons being, the nonavailability of a facial image database highlighting the spectacle problems.
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This database has five different linter quality classes (short cotton fibers), linter has wide applicability in the production of surgical tissue, paper money among other applications. The images available were used to classify the product in an industrial process, through the use of computer vision techniques.
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Stereolithographic files of three different mesh designs; Square, Triangular and Hexagonal (top to bottom rows in image). Each mesh design is provided in three different deformations; Flat/no deformation, Mode 1 deformation and Mode 5 deformation (left to right columns in image). Mode 1 and Mode 5 deformation was obtained by modal study with the four outer surfaces of the frame fixed. Note that the out-of-plane deformation has been scaled to better proportions.
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