Data classifier for classifying pattern data into clusters

Image analysis – Learning systems – Trainable classifiers or pattern recognizers

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C382S225000

Reexamination Certificate

active

10375136

ABSTRACT:
A data classifier classifies a plurality of input pattern data into one or more clusters. For each pattern data, a cluster to which the pattern data belongs is provisionally determined. For each cluster, a predetermined correlation value is calculated between one or more pattern data belonging to the cluster and observational pattern data which is a target to be classified into a cluster. A cluster to which the observational pattern data belongs is determined based on the correlation values.

REFERENCES:
patent: 5479570 (1995-12-01), Imagawa et al.
patent: 5703964 (1997-12-01), Menon et al.
patent: 6094653 (2000-07-01), Li et al.
patent: 6108446 (2000-08-01), Hoshen
patent: 6650779 (2003-11-01), Vachtesvanos et al.
patent: 6778705 (2004-08-01), Gutta et al.
patent: 6904423 (2005-06-01), Nicolaou et al.
patent: 2003/0158828 (2003-08-01), Ikeda et al.
patent: A 7-234854 (1995-09-01), None
patent: A 8-36557 (1996-02-01), None
patent: A 2002-190025 (2002-07-01), None
patent: A 2002-329188 (2002-11-01), None
Kohonen, “Self-Organized Formation of Topologically Correct Feature Maps”, Biological Cybernetics, vol. 43, pp. 59-69, 1982.
Ultsch et al., “Knowledge Extraction from Artificial Neural Networks and Applications”, Proc. Transputer Anwender Treffen/ World Transputer Congress TAT/WTC 93 Aachen, Springer, 1993.
Coomans et al., “Potential Methods in Pattern Recognition Part 2. CLUPOT—an Unsupervised Pattern Recognition Technique”, Analytica Chimica Acta, vol. 133, pp. 225-239, 1981.
Terashima et al., “Unsupervised Cluster Segmentation Method Using Data Density Histogram on Self-Organizing Feature Map”, Papers of the Institute of Electronics, Information, and Communication Engineers, D-II, vol. J79-D-II, No. 7, pp. 1280-1290, 1996.
Kirk et al., “A Self-Organizing Map with Dynamic Architecture for Efficient Quantization”, IEEE, pp. 2128-2132, 2001.
Bauer et al., “Quantifying the Neighborhood Preservation of Self-Organizing Feature Maps”, IEEE Transactions on Neural Networks, vol. 3, No. 4, pp. 570-579, 1992.
Martinetz et al., “Three-Dimensional Neural Net for Learning Visuomotor Coodination of a Robot Arm”, IEEE Transactions on Neural Networks, vol. 1, No. 1, pp. 131-136, 1990.
Kohonen, “The Self-Organizing Map”, Proceedings of the IEEE, vol. 78, No. 9, pp. 1464-1480, 1990.
Haese et al., “Auto-SOM: Recursive Parameter Estimation for Guidance of Self-Organizing Feature Maps”, Neural Computation, vol. 13, pp. 595-619, 2001.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Data classifier for classifying pattern data into clusters does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Data classifier for classifying pattern data into clusters, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Data classifier for classifying pattern data into clusters will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-3814742

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.