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When applying an SVM classifier (i.e., in the second and third modes), we employ the one-against-one approach described in [17] to convert binary outputs from the SVM classifier into the desired multiclass form where we must discriminate among vehicles, people, and noise.
It corresponds to a logical 'OR' operator applied to the binary outputs from the channels.
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In general, discretization based on static bit allocation assigns n bits equally to each of the D feature dimensions, thereby yielding a Dn-bit binary string in representing every identity upon concatenating short binary outputs from all individual dimensions.
Eventually, the binary output from each dimension is concatenated to form the user's final bit string.
Logic gates compute a binary output from one or more binary inputs.
And the rest seven pins from the microcontroller are used to send binary outputs to control the seven segment led display one at a time.
Each user transmits by QPSK modulation to generate the symbols from the binary output of the convolutional encoder.
The binary outputs can be controlled by the driver or can be configured to be an alarm output controlled by the corresponding thermocouple input.
When a discriminant function f[ l | m ] (x) is determined from a learning data set X[ l | m ] = {(x(n ), t(n )) ∈ X| t(n ) ∈ l ∪ m}, the binary output function of the classifier is described as follows.
In this system, each input pixel, from the continuous tone image, to the quantizer is compared against a threshold to determine its binary output in the halftoned image.
At the same time, the binary output can also be obtained from the systems that provide the continuous probabilistic output.
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