Open Access. Powered by Scholars. Published by Universities.®

Other Computer Sciences Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 3 of 3

Full-Text Articles in Other Computer Sciences

Underwater Computer Vision - Fish Recognition, Spencer Chang, Austin Otto Jun 2017

Underwater Computer Vision - Fish Recognition, Spencer Chang, Austin Otto

Computer Engineering

The Underwater Computer Vision – Fish Recognition project includes the design and implementation of a device that can withstand staying underwater for a duration of time, take pictures of underwater creatures, such as fish, and be able to identify certain fish. The system is meant to be cheap to create, yet still able to process the images it takes and identify the objects in the pictures with some accuracy. The device can output its results to another device or an end user.


Procedurally Generating Genetic Keys, Adam A. Levasseur Jun 2017

Procedurally Generating Genetic Keys, Adam A. Levasseur

Computer Engineering

This project presents a method for creating multi-part models based on input keys to generate new, variant models via genetic algorithms. By utilizing 3D models as modular parts, this method allows for the generation of a unique, compound model based on one or multiple input keys. This paper explains the process of creating and testing such generation styles using simple geometry to create more complex, compound models.


Automated Grading Of Handwritten Numerical Answers, Mark T. Brown Jun 2017

Automated Grading Of Handwritten Numerical Answers, Mark T. Brown

Computer Engineering

The objective of this project was to automate the process of grading handwritten numerical answers in a classroom setting. The final program accepts a scanned answer sheet completed by the student along with a description of the correct answers and produces a detailed report describing the confidence of correctness for each answer.

Computer vision techniques are used to automatically locate the locations of the answers in the scan. Each digit is then passed through a convolutional neural network to predict what was written by the student. The individual probabilities of each digit produced by the network are aggregated into a …