Matt Lohens is excited to announce the kickoff of a new project in the University of Utah's Deep Learning Capstone program. The project, which aims to improve the ability of ski resorts to detect and prevent fraudulent activity, was inspired by Matt's experience with electronic ski pass systems and their growing popularity in the ski industry.
One such system, manufactured by Axess, is used by Deer Valley and Solitude Resorts. In an effort to improve these resorts' ability to detect pass misuse and protect against lost revenue, Matt proposed the development of a deep learning-based ski pass misuse detection system.
The proposed system will be trained and tested using clothing datasets, and will be evaluated on actual ski lift camera data from Deer Valley and Solitude Resorts. By accurately and efficiently detecting fraudulent activity, such as the unauthorized use of passes or the use of altered or forged passes, this solution has the potential to significantly benefit the resorts and enhance the experience of legitimate pass holders.
Matt is excited to work with Deer Valley and Solitude Resorts, and the University of Utah to develop and implement this solution, and is confident that it will make a positive impact in the ski industry.
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