Engineering Commons^™

Modeling And Analysis Of Subcellular Protein Localization In Hyper-Dimensional Fluorescent Microscopy Images Using Deep Learning Methods, Yang Jiao

UNLV Theses, Dissertations, Professional Papers, and Capstones

Hyper-dimensional images are informative and become increasingly common in biomedical research. However, the machine learning methods of studying and processing the hyper-dimensional images are underdeveloped. Most of the methods only model the mapping functions between input and output by focusing on the spatial relationship, whereas neglect the temporal and causal relationships. In many cases, the spatial, temporal, and causal relationships are correlated and become a relationship complex. Therefore, only modeling the spatial relationship may result in inaccurate mapping function modeling and lead to undesired output. Despite the importance, there are multiple challenges on modeling the relationship complex, including the model …

Water Quality Prediction Based On Machine Learning Techniques, Zhao Fu

UNLV Theses, Dissertations, Professional Papers, and Capstones

Water is one of the most important natural resources for all living organisms on earth. The monitoring of treated wastewater discharge quality is vitally important for the stability and protection of the ecosystem. Collecting and analyzing water samples in the laboratory consumes much time and resources. In the last decade, many machine learning techniques, like multivariate linear regression (MLR) and artificial neural network (ANN) model, have been proposed to address the problem. However, simple linear regression analysis cannot accurately forecast water quality because of complicated linear and nonlinear relationships in the water quality dataset. The ANN model also has shortcomings …

Neural Network In Hardware, Jiong Si

UNLV Theses, Dissertations, Professional Papers, and Capstones

This dissertation describes the implementation of several neural networks built on a field programmable gate array (FPGA) and used to recognize a handwritten digit dataset – the Modified National Institute of Standards and Technology (MNIST) database. A novel hardwarefriendly activation function called the dynamic ReLU (D-ReLU) function is proposed. This activation function can decrease chip area and power of neural networks when compared to traditional activation functions at no cost to prediction accuracy.

The implementations of three neural networks on FPGA are presented: 2-layer online training fully-connected neural network, 3-layer offline training fully-connected neural network, and two solutions of Super-Skinny …

On Action Quality Assessment, Paritosh Parmar

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this dissertation, we tackle the task of quantifying the quality of actions, i.e., how well an

action was performed using computer vision. Existing methods used human body pose-based features to express the quality contained in an action sample. Human body pose estimation in actions such as sports actions, like diving and gymnastic vault, is particularly challenging, since the athletes undergo convoluted transformations while performing their routines. Moreover, pose-based features do not take into account visual cues such as water splash in diving. Visual cues are taken into account by human judges. In our first work, we show that using …