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Synthetic-aperture sonar (SAS) is a form of sonar in which sophisticated post-processing of sonar data is used in ways closely analogous to synthetic-aperture radar. Synthetic-aperture sonars combine a number of acoustic pings to form an image with much higher along-track resolution than conventional sonars.
THz and thermal video data set This multispectral data set includes terahertz, thermal, visual, near infrared, and three-dimensional videos of objects hidden under people's clothes. images and 3D point clouds More than 20 videos. The duration of each video is about 85 seconds (about 345 frames). AP2J Experiments with hidden object detection 2019
Car Evaluation Data Set Car properties and their overall acceptability. Six categorical features given. 1728 Text Classification 1997 [13] [14] M. Bohanec YouTube Comedy Slam Preference Dataset User vote data for pairs of videos shown on YouTube. Users voted on funnier videos. Video metadata given. 1,138,562 Text Classification 2012 [15] [16 ...
SAS/GRAPH, which produces graphics, was released in 1980, as well as the SAS/ETS component, which supports econometric and time series analysis. A component intended for pharmaceutical users, SAS/PH-Clinical, was released in the 1990s. The Food and Drug Administration standardized on using SAS/PH-Clinical for new drug applications in 2002. [20]
The Robotics Toolbox for Python is a reimplementation of the Robotics Toolbox for MATLAB for Python 3. [7] [8] Its functionality is a superset of the Robotics Toolbox for MATLAB, the programming model is similar, and it supports additional methods to define a serial link manipulator including URDF and elementary transform sequences.
The SAS macro language is made available within base SAS software to reduce the amount of code, and create code generators for building more versatile and flexible programs. [21] The macro language can be used for functionalities as simple as symbolic substitution and as complex as dynamic programming . [ 8 ]
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
The higher voltage offers (among other features) the ability to use SAS in server backplanes. [12] Because of its higher signaling voltages, SAS can use cables up to 10 m (33 ft) long, whereas SATA has a cable-length limit of 1 m (3.3 ft) or 2 m (6.6 ft) for eSATA. [12] SAS is full duplex, whereas SATA is half duplex. The SAS transport layer ...