To demonstrate the potential of compression-based similarity measures we propose an algorithm that is based on finite-context models and works directly on the ...
To demonstrate the potential of compression-based similarity measures we propose an algorithm that is based on finite-context models and works directly on the ...
To demonstrate the potential of compression-based similarity measures we propose an algorithm that is based on finite-context models and works directly on the ...
Sep 11, 2011 · To demonstrate the potential of compression-based similarity measures we propose an algorithm that is based on finite-context models and works ...
Jan 31, 2018 · This paper investigates the usefulness of the normalized compression distance (NCD) for image similarity detection.
In this paper, we will concentrate on a new, algorithmic complexity-based metric called Normalized Compression Distance. It is a universal distance used to ...
May 7, 2013 · A new line of research uses compression methods to measure the similarity between signals. Two signals are considered similar if one can be ...
People also ask
What is the normalized compression distance?
How to measure similarity of images?
For certain transforms and compressors, the proposed approach appears to provide robustness at similarity detection against smoothing, lossy compression, ...
To this end, we introduce a similarity metric which focuses on the shared patterns between two sequences based on normalized compression distance. In short, ...
This paper investigates the usefulness of the normalized compression distance (NCD) for image similarity detection. Instead of the direct NCD between images ...