Lenamalena

Lenamalena

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Lenamalena's repositories

BeechFood

viewing the contents of the trash cans

Face_in_Mask-Detector

Masked face recognition

KMeans

Adaptive clustering algorithms allow us to obtain the best clustering parameters in terms of determining cluster centers, as well as their number)

BaiesClassification

The Bayes formula is the ratio of the product of the probability of one of the events of the system to the conditional probability of this event relative to the corresponding event of the system to the total probability of the occurrence of event A taking into account all the events of the system

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Convolution-of-input-signal

Convolution describes the interaction of signals among themselves. If one of the signals is the pulse characteristic of the filter, then the convolution of the input sequence with the pulse characteristic is the reaction of the circuit to the input effect

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DatabaseSTD

Simple SQL database, student information

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fourier-transform-sound

Fourier analysis lays the foundations for many methods used in the field of digital signal processing))) The Fourier transform (in fact, there are several variants of such transformations) allows you to match a signal given in the time domain with its equivalent representation in the frequency domain. On the contrary, if the frequency response of the signal is known, then the inverse Fourier transform allows you to determine the corresponding signal in the time domain.

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LeJandrDecisionFuncton

FOR RECOGNITION If classes are inseparable in a linear way, then nonlinear decision functions can be used for classification. When constructing such functions, the apparatus of representing an arbitrary function with the help of series according to the system of orthogonal functions of several variables can be used

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OneEtalonClassification

Image classification using distance functions is one of the first ideas of automatic image recognition. This classification method turns out to be a very effective tool in solving such problems in which classes are characterized by a degree of variability limited within reasonable limits. The choice of distance functions as a classification tool is a natural consequence of the fact that the most obvious way to introduce a similarity measure for image vectors interpreted as points in Euclidean space is to determine their proximity

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