返回
Off-line hand written input based identity determination using multi kernel feature combination
DOI:10.1016/j.patrec.2013.04.032.png)
摘要
En 中文
The paper presents a novel framework for the application of multiple features for handwritten data based identity recognition. Different types of features characterise different facets of the handwriting. We have designed a scheme for multiple feature based identity establishment using multi-kernel learning. A new formulation for multi-kernel learning using genetic algorithm has been presented. The efficacy of the framework using individual and combination of features is demonstrated for Devanagari script input. (C) 2013 Elsevier B.V. All rights reserved.
Keyword:
Multiple kernel learning
Writer identification
Writer verification
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.3
论文数:
8.0K
被引数:
1.6W
机构
引用论文
Influence of environmental factors on slender amaranth (Amaranthus viridis) germination
Weed Science
IF0
Scaling and rotation invariant analysis approach to object recognition based on Radon and Fourier-Mellin transforms
PATTERN RECOGNITION
IF7.6
Reducing forgeries in writer-independent off-line signature verification through ensemble of classifiers
PATTERN RECOGNITION
IF7.6

