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Neural Network In Hardware, Jiong Si
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
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 …