PROVIDING CLASSES AT PRESCHOOL

Brand Owner (click to sort) Address Description
CHILDREN'S DISCOVERY CENTERS KINDERCARE EDUCATION 650 N.E. Holladay St., Ste. 1400 Portland OR 97232 providing classes at the preschool level;Childrens Discovery Centers;CHILDREN'S AND CENTERS;providing daycare services;
DISCOVERY EXPRESS Children's Discovery Center, Inc. 1110 Venning Road Mt. Pleasant SC 29464 providing classes at the preschool level;children's day-care services;
DISCOVERY KIDZ DISCOVERY EXPRESS FRANCHISE COMPANY 3905 TALMADGE ROAD TOLEDO OH 43606 providing classes at the preschool level;DISCOVERY KIDS;providing childrens day-care services;
PIAGET DISCOVERY SCHOOL CHILDREN'S DISCOVERY CENTERS OF AMERICA, INC. 4340 REDWOOD HIGHWAY, BUILDING B San Rafael CA 949032121 providing classes at the preschool level;In the statement, Column 2, line 4, preschool is deleted, and, school is inserted. The drawing is amended to appear as follows: PIAGET DISCOVERY SCHOOL;SCHOOL;providing daycare services;
PROJECT DISCOVERY DISCOVERY EXPRESS FRANCHISE COMPANY 3905 TALMADGE ROAD TOLEDO OH 43606 providing classes at the preschool level;providing childrens day-care services;
WHAT CHILD CARE WAS MEANT TO BE Children's Discovery Center, Inc. 1110 Venning Road Mt. Pleasant SC 29464 providing classes at the preschool level;providing children's day-care services;
WHERE CHILDREN LEARN THROUGH EXPLORATION Children's Discovery Center, Inc. 1110 Venning Road Mt. Pleasant SC 29464 providing classes at the preschool level;providing children's day-care services;
 

Where the owner name is not linked, that owner no longer owns the brand

    
Technical Examples
  1. The present invention recites a method and computer program product for identifying one or more new pattern classes and incorporating the classes into a pattern recognition classifier as output classes. A plurality of input patterns determined not to be associated with any of a set of at least one represented output class by a pattern recognition classifier are rejected. The rejected pattern samples are then grouped into clusters according to the similarities between the pattern samples. Clusters that represent new pattern classes are identified via independent review. The classifier is then retrained to include the new pattern classes as output classes.