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Full-Text Articles in Signal Processing
Automated Detection Of Hematological Abnormalities Through Classification Of Flow Cytometric Data Patterns, Mark A. Rossman
Automated Detection Of Hematological Abnormalities Through Classification Of Flow Cytometric Data Patterns, Mark A. Rossman
FIU Electronic Theses and Dissertations
Flow Cytometry analyzers have become trusted companions due to their ability to perform fast and accurate analyses of human blood. The aim of these analyses is to determine the possible existence of abnormalities in the blood that have been correlated with serious disease states, such as infectious mononucleosis, leukemia, and various cancers. Though these analyzers provide important feedback, it is always desired to improve the accuracy of the results. This is evidenced by the occurrences of misclassifications reported by some users of these devices. It is advantageous to provide a pattern interpretation framework that is able to provide better classification …
A Highly Efficient Biometrics Approach For Unconstrained Iris Segmentation And Recognition, Yu Chen
A Highly Efficient Biometrics Approach For Unconstrained Iris Segmentation And Recognition, Yu Chen
FIU Electronic Theses and Dissertations
This dissertation develops an innovative approach towards less-constrained iris biometrics. Two major contributions are made in this research endeavor: (1) Designed an award-winning segmentation algorithm in the less-constrained environment where image acquisition is made of subjects on the move and taken under visible lighting conditions, and (2) Developed a pioneering iris biometrics method coupling segmentation and recognition of the iris based on video of moving persons under different acquisitions scenarios. The first part of the dissertation introduces a robust and fast segmentation approach using still images contained in the UBIRIS (version 2) noisy iris database. The results show accuracy estimated …