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Full-Text Articles in Engineering
Machine Learning Applications In Plant Identification, Wireless Channel Estimation, And Gain Estimation For Multi-User Software-Defined Radio, Viraj K. Gajjar
Machine Learning Applications In Plant Identification, Wireless Channel Estimation, And Gain Estimation For Multi-User Software-Defined Radio, Viraj K. Gajjar
Doctoral Dissertations
"This work applies machine learning (ML) techniques to selected computer vision and digital communication problems. Machine learning algorithms can be trained to perform a specific task without explicit programming. This research applies ML to the problems of: plant identification from images of leaves, channel state information (CSI) estimation for wireless multiple-input-multiple-output (MIMO) systems, and gain estimation for a multi-user software-defined radio (SDR) application.
In the first task, two methods for plant species identification from leaf images are developed. One of the methods uses hand-crafted features extracted from leaf images to train a support vector machine classifier. The other method combines …
Detecting, Segmenting And Tracking Bio-Medical Objects, Mingzhong Li
Detecting, Segmenting And Tracking Bio-Medical Objects, Mingzhong Li
Doctoral Dissertations
"Studying the behavior patterns of biomedical objects helps scientists understand the underlying mechanisms. With computer vision techniques, automated monitoring can be implemented for efficient and effective analysis in biomedical studies. Promising applications have been carried out in various research topics, including insect group monitoring, malignant cell detection and segmentation, human organ segmentation and nano-particle tracking.
In general, applications of computer vision techniques in monitoring biomedical objects include the following stages: detection, segmentation and tracking. Challenges in each stage will potentially lead to unsatisfactory results of automated monitoring. These challenges include different foreground-background contrast, fast motion blur, clutter, object overlap and …