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A Privacy Preserving Online Learning Framework For Medical Diagnosis Applications, Trang Pham Ngoc Nguyen
A Privacy Preserving Online Learning Framework For Medical Diagnosis Applications, Trang Pham Ngoc Nguyen
Theses: Doctorates and Masters
Electronic Health records are an important part of a digital healthcare system. Due to their significance, electronic health records have become a major target for hackers, and hospitals/clinics prefer to keep the records at local sites protected by adequate security measures. This introduces challenges in sharing health records. Sharing health records however, is critical in building an accurate online diagnosis framework. Most local sites have small data sets, and machine learning models developed locally based on small data sets, do not have knowledge about other data sets and learning models used at other sites.
The work in this thesis utilizes …
Application Of Advanced Algorithms And Statistical Techniques For Weed-Plant Discrimination, Saman Akbar Zadeh
Application Of Advanced Algorithms And Statistical Techniques For Weed-Plant Discrimination, Saman Akbar Zadeh
Theses: Doctorates and Masters
Precision agriculture requires automated systems for weed detection as weeds compete with the crop for water, nutrients, and light. The purpose of this study is to investigate the use of machine learning methods to classify weeds/crops in agriculture. Statistical methods, support vector machines, convolutional neural networks (CNNs) are introduced, investigated and optimized as classifiers to provide high accuracy at high vehicular speed for weed detection.
Initially, Support Vector Machine (SVM) algorithms are developed for weed-crop discrimination and their accuracies are compared with a conventional data-aggregation method based on the evaluation of discrete Normalised Difference Vegetation Indices (NDVIs) at two different …