Most likely state - The most likely state is a state assigned the greatest probability by an agent's current probability distribution over possible states.
Most probable explanation - A most probable explanation, or MPE, is a joint assignment to all unobserved variables that has the highest probability given the observed evidence in a...
Motion analysis - Motion analysis is the study of movement over time using observations such as video frames, tracked points, or sensor measurements.
Motion blur - Motion blur is the smearing of image detail caused by movement during the time an image sensor collects light.
Motion capture - Motion capture is the recording of a person's or object's movement as digital motion data.
Motion coding - Motion coding is the representation of motion-related information in a compressed video stream so that a decoder can predict image content from reference...
Motion compensation - Motion compensation uses motion information to form a prediction of image content from one or more reference images.
Motion estimation - Motion estimation is the process of estimating how image content changes position between frames or views.
Motion field - A motion field is a spatial collection of motion vectors.
Motion-JPEG - Motion-JPEG, often written MJPEG or M-JPEG, represents video as a sequence of separately JPEG-compressed images.
Motion model - A motion model describes how the state of a moving object or robot changes over time, often in response to control inputs.
Motion planning - Motion planning is the process of finding a feasible movement from a robot's starting configuration to a goal while respecting relevant constraints.
Motion vector - A motion vector is a numerical description of movement between positions, usually expressed as horizontal and vertical displacement in an image.
Move generation - Move generation is the process of producing the candidate or legal actions available from a game position or search state.
Move-to-front transform - The move-to-front transform, or MTF, is a reversible transformation that replaces each input symbol with its current position in an ordered list, then moves...
Moving average - A moving average is an average recalculated over a window that moves through a sequence of observations.
Moving average crossover - A moving average crossover occurs when one moving average moves from one side of another moving average to the other.
Moving object detection - Moving object detection is the identification of image regions or objects that are moving over time.
MRF optimization via dual decomposition - MRF optimization via dual decomposition is a framework for minimizing a discrete Markov random field's energy by splitting it into easier subproblems and...
MS between groups (MS group ) - MS between groups, also written MS group or between-groups mean square, is the between-groups sum of squares divided by its degrees of freedom in an...
MS-SSIM - MS-SSIM, or multiscale structural similarity, is a full-reference image-quality measure that compares a test image with a reference at several spatial scales.
MS within (MS error ) - MS within, also called MS error or the within-groups mean square in a basic one-way ANOVA, is the within-groups sum of squared deviations divided by its...
MTD(f) - MTD(f) is a minimax search algorithm that repeatedly calls a memory-enhanced alpha-beta search with a narrow, zero-window test until lower and upper bounds...
Mu-law - Mu-law, written μ-law, is a nonlinear companding method used to represent audio amplitudes with relatively fine resolution near zero and coarser resolution...
MUC F-measure - MUC F-measure is a coreference evaluation score that combines MUC precision and recall.
Multi-agent collaboration - Multi-agent collaboration is the coordination of several AI agents that work together on a shared task, communicating and dividing work so the group...
Multi-attribute global inference of quality - Multi-attribute global inference of quality, usually abbreviated MAGIQ, is a decision-analysis method that combines rankings on several attributes into an...
Multi-class - Multi-class describes a classification setting where each item belongs to exactly one of three or more categories: a ticket routed to one of ten teams, a...
Multi-class classification - Multi-class classification is the task of assigning each item to exactly one category from three or more: routing a ticket to one of ten teams, tagging a...
Multi-class logistic regression - Multi-class logistic regression is a classification method that estimates probabilities for more than two mutually exclusive outcome categories.
Multi-document summarization - Multi-document summarization is the task of producing a concise account from information in several source documents.
Multi expression programming - Multi expression programming is an evolutionary programming method that represents several candidate expressions within one linear chromosome.
Multi-head attention - Multi-head attention is an attention mechanism that performs several learned attention operations in parallel and combines their outputs.
Multi-head self-attention - Multi-head self-attention is an attention operation in which several heads build contextual representations by comparing positions within the same input...
Multi-label - Multi-label describes a setting where each item can carry several labels at once: a photo tagged beach and sunset and family, a ticket marked billing and...
Multi-label classification - Multi-label classification is the task of assigning each item a set of labels, from zero to many: tagging a document with all its topics, flagging a...
Multi-level security - Multi-level security is an approach to processing information with different security classifications and categories while allowing authorized users...
Multi-model database - A multi-model database supports more than one way of organizing and working with data within one database system.
Multi-objective optimization - Multi-objective optimization studies decisions with two or more objectives that may conflict, such as reducing prediction error and reducing computing cost.
Multi-output - Multi-output describes a prediction problem in which each input example has more than one target value, such as several numerical measurements or...
Multi-party authorization - Multi-party authorization is an arrangement in which a protected action requires approval from more than one authorized party.
Multi-spectral image - A multi-spectral image records a scene in several wavelength bands of electromagnetic radiation.
Multi-surface method - The multi-surface method is a historical approach to classifying patterns by constructing several separating surfaces.
Multi-task Elastic-Net - Multi-task Elastic-Net is a regression method that learns several related prediction tasks together, mixing two penalties so the tasks share a common set of...
Multi-task Lasso - Multi-task Lasso is a regression method that learns several related tasks together under a shared sparsity penalty: a field is kept or evicted for the whole...
Multiagent planning problem - A multiagent planning problem is the challenge of getting several agents to produce and follow a coordinated plan, when each agent has its own capabilities...