The purpose of this study is to develop a flexible matching method for recognizing handwritten numerals based on the statistics of shapes and structures learned from learning sam...
This paper presents a segmentation-based handwriting recognizer and the performance that it achieves on the numerical fields extracted from a large single-writer historical collec...
Marius Bulacu, Axel Brink, Tijn van der Zant, Lamb...
—Deformable models have recently been proposed for many pattern recognition applications due to their ability to handle large shape variations.These proposed approaches represent...
This paper studies on the mirror image learning algorithm for the autoassociative neural networks and evaluates the performance by handwritten numeral recognition test. Each of th...
Currently, most of the discovered biological and biomedical knowledge is available as textual data in scientific papers. And, locating and curating information about a genomic enti...