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The SKYNET project was linked with drone systems, thus creating the potential for false-positives to lead to deaths. [1] [5]According to NSA, the SKYNET project is able to accurately reconstruct crucial information about the suspects including their social relationships, habits, and patterns of movements through graph-based visualization of GSM data. [3]
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]
Machine learning of visual recognition relates to patterns and their classification. [5] [6] True video analytics can distinguish the human form, vehicles and boats or selected objects from the general movement of all other objects and visual static or changes in pixels on the monitor. It does this by recognizing patterns. When the object of ...
Empirically, for machine learning heuristics, choices of a function that do not satisfy Mercer's condition may still perform reasonably if at least approximates the intuitive idea of similarity. [6] Regardless of whether k {\displaystyle k} is a Mercer kernel, k {\displaystyle k} may still be referred to as a "kernel".
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]
Countersurveillance refers to measures that are usually undertaken by the public to prevent surveillance, [1] including covert surveillance.Countersurveillance may include electronic methods such as technical surveillance counter-measures, which is the process of detecting surveillance devices.
There is a growing body of literature on methods of exploiting AIS data for safety and optimisation of seafaring, namely traffic analysis, anomaly detection, route extraction and prediction, collision detection, path planning, weather routing, atmospheric refractivity estimation and many more [72] [73] [74] [75]
Predictive analytics statistical techniques include data modeling, machine learning, AI, deep learning algorithms and data mining. Often the unknown event of interest is in the future, but predictive analytics can be applied to any type of unknown whether it be in the past, present or future.