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This allowed detecting the match by maintaining just one element of the sample scene.
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To be able to detect the match, therefore, it was necessary to maintain a detailed record of all objects in the scene as well their associative-configural arrangement.
To detect the matching pair using the sensors, the strands of DNA in the test solution must contain a magnetic particle.
A novel acceleration algorithm for SIFT implementation based on Compute Unified Device Architecture (CUDA) is presented to detect the matching feature points in 2D images.
In order to detect the matching point pairs of (p i, p j ), we initially evaluate the set of measurements {m k (p i, p j )}.
In short, a BLAST search is performed starting with a protein sequence from organism A to detect the matching sequences in organism B. Then, the sequence from B displaying the highest score is compared (reverse BLAST) against the all sequences of A and the highest scoring hit must be the initial sequence.
RMA starts with a non-linear background correction based on a single chip to detect the perfect match signal.
The sensor could detect the perfectly matched target, in the background of the mismatched target or other oligonucleotides of random sequences.
Two ways of applying HCF are further proposed in [11] to detect the LSB matching steganography in gray-scale images.
So the steganalytic algorithms in [11] to detect the LSB matching steganography and the SPA steganalysis in [9] to detect the random LSB hiding are prevented in principle.
In [11], two ways of applying the HCF are further proposed to detect the LSB matching steganography in the gray-scale images.
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