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Full-Text Articles in Engineering
Statistical Machine Learning For Breast Cancer Detection With Terahertz Imaging, Tanny Andrea Chavez Esparza
Statistical Machine Learning For Breast Cancer Detection With Terahertz Imaging, Tanny Andrea Chavez Esparza
Graduate Theses and Dissertations
Breast conserving surgery (BCS) is a common breast cancer treatment option, in which the cancerous tissue is excised while leaving most of the healthy breast tissue intact. The lack of in-situ margin evaluation unfortunately results in a re-excision rate of 20-30% for this type of procedure. This study aims to design statistical and machine learning segmentation algorithms for the detection of breast cancer in BCS by using terahertz (THz) imaging. Given the material characterization properties of the non-ionizing radiation in the THz range, we intend to employ the responses from the THz system to identify healthy and cancerous breast tissue …
Analog Spiking Neural Network Implementing Spike Timing-Dependent Plasticity On 65 Nm Cmos, Luke Vincent
Analog Spiking Neural Network Implementing Spike Timing-Dependent Plasticity On 65 Nm Cmos, Luke Vincent
Graduate Theses and Dissertations
Machine learning is a rapidly accelerating tool and technology used for countless applications in the modern world. There are many digital algorithms to deploy a machine learning program, but the most advanced and well-known algorithm is the artificial neural network (ANN). While ANNs demonstrate impressive reinforcement learning behaviors, they require large power consumption to operate. Therefore, an analog spiking neural network (SNN) implementing spike timing-dependent plasticity is proposed, developed, and tested to demonstrate equivalent learning abilities with fractional power consumption compared to its digital adversary.