About | Vendi

Who We Are

Team #23

Welcome to our team's About Us page! We are a group of passionate developers who came together to create a mobile app that makes it easy to find vending machines in your area. Our app was thought of when we noticed how many people on campus tend to look for vending machines on campus.

Because of this, we decided to put our heads together and develop a solution to this problem. We spent countless hours researching, designing, and coding to bring our idea to life. Our team is made up of CS students from UNR who have worked tirelessly to create an app that is user-friendly, reliable, and accurate.

The Developers

Joe Paschke

Maxwell Synard

Catherine Wedin

Charles Dunn

Advisors and Managers

Clayton Synard

Demitri Bannoura

Instructor: David Feil-Seifer

Instructor: Devrin Lee

The Faculty

Resources

Flutter Apprentice

The book describes the different ways one can use the Google framework, Flutter, to develop apps. It goes over UI development, using SQLite, developing using states, and deploying the app.

Link To Book

Flutter Documentation

The flutter site has a great deal of documentation that even the book doesn't cover. It also covers documentation on popular plugins that aren't natively in the framework.

Link To Website

FireBase Documentation

As the primary part of our backend Firebase was a very important aspect of our app. The documentation for Firebase gave us new ideas on what we could do with that app as well as what we needed for our current ideas.

Link To Website

Tensorflow Documentation

Tensorflow was used in the creation, building, and interpreting our model was an integral part of our app. The documentation made choosing the many settings of my model easier as well as creating an interpreter for it.

Link To Website

A study on Image Classification based on Deep Learning and Tensorflow

A paper discussing the usage of machine learning in the problem of image classification. This paper helped with choosing a machine learning model and shows how image classification works in a very simple way

Link To Paper