Object recognition of Leukemia affected cells using DCC and IFS

J. Joe, T. Ravi, A. Natarajan, S. Kumar
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引用次数: 1

Abstract

Discriminative Canonical Correlations (DCC) technique is used to compare sets of images for Object Recognition. Canonical Correlations can be thought of as the angles between two d-dimensional subspaces, have recently attracted attention for image set matching. This technology is coupled with Iterated Function System (IFS) for images. This algorithm holds good for the fractal images to be compressed in a better way for the existing image set database. In this manuscript, how the Leukemia affected cells can be detected by using Discriminative Canonical Correlations technique coupled with Iterated Function Systems.
DCC和IFS在白血病细胞目标识别中的应用
判别典型相关(DCC)技术用于图像集的比较,用于目标识别。典型相关可以被认为是两个d维子空间之间的角度,最近引起了人们对图像集匹配的关注。该技术与图像迭代函数系统(IFS)相结合。该算法适用于现有图像集数据库对分形图像进行更好的压缩。在这篇文章中,如何使用鉴别典型相关技术结合迭代函数系统来检测白血病细胞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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