Set redundancy compression - Set redundancy compression refers to methods that exploit information shared across a collection of similar data items, especially images.
Set semantics - Set semantics interprets a collection through set membership: an item is either present or absent, and repeated copies do not add meaning.
SGNS - SGNS stands for skip-gram with negative sampling, a method for learning word embeddings by distinguishing observed word - context pairs from sampled noise...
Shadow removal - Shadow removal is the process of producing an image or representation in which the effects of selected shadows are reduced or compensated for.
Shallow Copy - A shallow copy creates a new outer object while retaining references to the objects held inside it.
Shallow learning - Shallow learning is an informal term for machine-learning approaches that do not rely on a long hierarchy of learned transformations.
Shampoo optimizer - Shampoo is an adaptive gradient optimizer that uses the matrix or tensor structure of model parameters to build manageable preconditioners.
Shannon coding - Shannon coding is a method for constructing a variable-length, prefix-free code from symbol probabilities.
Shannon - Fano coding - Shannon - Fano coding commonly refers to a variable-length prefix-code construction that sorts symbols by probability and repeatedly splits them into two...
Shannon - Fano - Elias coding - Shannon - Fano - Elias coding is a prefix-code construction that assigns each symbol a probability interval, takes that interval's midpoint, and represents...
Shannon's source coding theorem - Shannon's source coding theorem establishes entropy as the fundamental rate limit for lossless compression under an appropriate source model.
Shape - Shape is the geometric form of an object or region, described through features such as its boundary, surface, proportions and arrangement of parts.
Shape from defocus - Shape from defocus estimates scene depth or surface shape from the way optical defocus changes image appearance.
Shape from focus - Shape from focus estimates depth or surface shape by analyzing local sharpness across images captured at different focus settings or relative camera -...
Shape from shading - Shape from shading estimates surface orientation or shape from brightness variations interpreted through a model of illumination and surface reflectance.
Shape grammar - A shape grammar is a formal system of spatial rules that generates or describes designs by matching and transforming shapes.
Shape (Tensor) - A tensor's shape lists the lengths of its axes in order. For example, shape (4,7,3) describes three axes containing four, seven and three positions.
Shaping theorem - The shaping theorem is a reinforcement-learning result showing that a particular form of added reward can preserve the set of optimal policies.
Shapiro-Wilk test - The Shapiro-Wilk test is a statistical test of whether a sample is compatible with a normal distribution.
Shard - A shard is a logical portion of a larger dataset, model or data structure that can be stored or processed separately.
Shared memory - Shared memory is memory that more than one execution context, such as threads or processes, can access.
Shared models - Shared models are trained machine-learning models made available for reuse by other developers, teams or applications.
Shared snapshot objects - Shared snapshot objects are concurrent data structures that let processes update components and obtain a coherent view of the components together.
Sharpening - Image sharpening is processing that increases the apparent definition of edges or fine detail, often by strengthening selected local intensity differences.
Shaving - Shaving is a constraint-programming technique that temporarily tests a possible variable value or domain restriction, propagates its consequences and...
Shear matrix - A shear matrix represents a transformation that slides points parallel to a fixed line or plane by amounts proportional to their distance from it.
Shi - Tomasi (good features to track) - The Shi - Tomasi feature-selection criterion scores a local image patch using the smaller eigenvalue of its gradient second-moment matrix.
Shift-invariant - In signal and image processing, a shift-invariant system responds to a translated input by producing the same translation of its original output.
Shift-Map editing - Shift-Map editing is an image-editing framework that assigns each output pixel a displacement identifying its source location in an input image.
Shift-reduce parsing - Shift-reduce parsing builds a grammatical analysis by moving input items onto a stack and combining items at the top of that stack into larger structures.
Shift theorem - The Fourier shift theorem describes how translating a signal changes its Fourier transform.
Shingling - Shingling represents a document using overlapping sequences of a fixed number of consecutive tokens.
Short-Time Fourier Transform - The Short-Time Fourier Transform, or STFT, represents how a signal's frequency content changes over time.
Shortest Augmenting Path - Shortest Augmenting Path is a maximum-flow approach that increases flow through a network by using short source-to-sink paths in the residual network.
Shortest Paths - Shortest paths are routes through a graph that minimize a defined total cost between specified nodes.
Shrinkage - Shrinkage is the deliberate pulling of estimated values toward a center, typically toward zero or a group average, trading a little bias for a large...
Sibilant sound - A sibilant sound contains prominent hissing or hushing frication produced by a directed stream of air in the front of the mouth.
Sibyl attack - A Sybil attack occurs when one controlling entity presents multiple identities to gain influence that a system intends to distribute among independent...
Side-by-side evaluation - Side-by-side evaluation compares two systems by judging their outputs for the same input.
Side sequence - A side sequence is a subsidiary stretch of conversation that temporarily interrupts an ongoing sequence before participants return to it.
Sideways move - A sideways move is a local-search step from one candidate state to a neighboring state with the same evaluation value.
Siegel - Tukey test - The Siegel-Tukey test is a nonparametric procedure for comparing the spread of two independent samples using specially assigned ranks.
Sigmoid - A sigmoid is an S-shaped mathematical function. In machine learning, the term usually refers to the logistic sigmoid, sigma(z) = 1/(1 + exp(minus z)).
Sigmoid layer - A sigmoid layer applies the logistic sigmoid function to each element of an input tensor, producing outputs between zero and one for finite inputs in exact...
Sigmoid perceptron - A sigmoid perceptron is a neural unit that forms a weighted sum of its inputs, adds a bias, and applies a sigmoid activation to produce a smooth output.
Sign test - The sign test is a nonparametric test based on whether observations lie above or below a specified value, or whether paired differences are positive or...
Signal detection theory - Signal detection theory is a framework for separating the ability to distinguish a meaningful signal from background noise from the decision rule used to...
Signal magnitude area - Signal magnitude area, commonly abbreviated SMA, is a feature that summarizes the absolute magnitude of a signal over a time window.