Search results
Results from the WOW.Com Content Network
The dataset is labeled with semantic labels for 32 semantic classes. over 700 images Images Object recognition and classification 2008 [56] [57] [58] Gabriel J. Brostow, Jamie Shotton, Julien Fauqueur, Roberto Cipolla RailSem19 RailSem19 is a dataset for understanding scenes for vision systems on railways. The dataset is labeled semanticly and ...
The datasets are classified, based on the licenses, as Open data and Non-Open data. The datasets from various governmental-bodies are presented in List of open government data sites. The datasets are ported on open data portals. They are made available for searching, depositing and accessing through interfaces like Open API. The datasets are ...
For example, a traditional dataset may have contained images of dogs, each of the same size and orientation. In contrast, LabelMe contains images of dogs in multiple angles, sizes, and orientations. Designed for recognizing objects embedded in arbitrary scenes instead of images that are cropped, normalized, and/or resized to display a single ...
The Caltech 101 data set was used to train and test several computer vision recognition and classification algorithms. The first paper to use Caltech 101 was an incremental Bayesian approach to one-shot learning, [ 4 ] an attempt to classify an object using only a few examples, by building on prior knowledge of other classes.
MATLAB (an abbreviation of "MATrix LABoratory" [22]) is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks.MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.
The dinosaur data set created by Alberto Cairo that inspired the creation of the Datasaurus Dozen. The first data set, in the shape of a Tyrannosaurus, that inspired the rest of the "datasaurus" data set was constructed in 2016 by Alberto Cairo. [7] [8] It was proposed by Maarten Lambrechts that this data set also be called "Anscombosaurus". [7]
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]
To illustrate, consider an example from Cook et al. where the analysis task is to find the variables which best predict the tip that a dining party will give to the waiter. [12] The variables available in the data collected for this task are: the tip amount, total bill, payer gender, smoking/non-smoking section, time of day, day of the week ...