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The Weissman score is a performance metric for lossless compression applications. It was developed by Tsachy Weissman, a professor at Stanford University, and Vinith Misra, a graduate student, at the request of producers for HBO's television series Silicon Valley, a television show about a fictional tech start-up working on a data compression algorithm.
Toggle Commercial products using micro-scale MOSFETs subsection 2.1 Products featuring 20 μm manufacturing process 2.2 Products featuring 10 μm manufacturing process
NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]
WebP's lossless compression, a newer algorithm unrelated to VP8, was designed by Google software engineer Jyrki Alakuijala. It uses advanced techniques such as dedicated entropy codes for different color channels, exploiting 2D locality of backward reference distances and a color cache of recently used colors.
The .ZIP file format was designed by Phil Katz of PKWARE and Gary Conway of Infinity Design Concepts. The format was created after Systems Enhancement Associates (SEA) filed a lawsuit against PKWARE claiming that the latter's archiving products, named PKARC, were derivatives of SEA's ARC archiving system. [3]
In the case of decreasing the pixel number (scaling down), this usually results in a visible quality loss. From the standpoint of digital signal processing, the scaling of raster graphics is a two-dimensional example of sample-rate conversion, the conversion of a discrete signal from a sampling rate (in this case, the local sampling rate) to ...
The process of feature selection aims to find a suitable subset of the input variables (features, or attributes) for the task at hand.The three strategies are: the filter strategy (e.g., information gain), the wrapper strategy (e.g., accuracy-guided search), and the embedded strategy (features are added or removed while building the model based on prediction errors).
Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that predicts whether a new example falls into one category. [87] An SVM training algorithm is a non- probabilistic , binary , linear classifier , although methods such as Platt scaling exist to use SVM in a ...