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Review Classification, Balraj Aujla Dec 2016

Review Classification, Balraj Aujla

Computer Science and Software Engineering

The goal of this project is to find a way to analyze reviews and determine the sentiment of a review. It uses various machine learning techniques in order to achieve its goals such as SVMs and Naive Bayes. Overall the purpose is to learn many different machine learning techniques, determine which ones would be useful for the project, then compare the results. Research is the foremost goal of the project, and it is able to determine the better algorithm for review classification, naive bayes or an SVM. In addition, an SVM which actually gave review’s scores rather than just classifying …


Automated Detection Of Deep-Sea Animals, Dallas J. Hollis, Duane Edgington, Danelle Cline Jul 2016

Automated Detection Of Deep-Sea Animals, Dallas J. Hollis, Duane Edgington, Danelle Cline

STAR Program Research Presentations

The Monterey Bay Aquarium Research Institute routinely deploys remotely operated underwater vehicles equipped with high definition cameras for use in scientific studies. Utilizing a video collection of over 22,000 hours and the Video Annotation and Reference System, we have set out to automate the detection and classification of deep-sea animals. This paper serves to explore the pitfalls of automation and suggest possible solutions to automated detection in diverse ecosystems with varying field conditions. Detection was tested using a saliency-based neuromorphic selective attention algorithm. The animals that were not detected were then used to tune saliency parameters. Once objects are detected, …