This is the list of projects for our UF CISE Summer Internship Project Course - please select a group (4 students) and a project: There can be two groups that have the same project.
1 Image Denoising with Single- and Multi-Layer Neural Networks
Description: Design and develop a single-layer neural network that is an auto-associative memory which inputs a noisy version of an image a, then outputs the noise-free version of a (on which the NN has been trained). Repeat for multi-layer NN and compare performance with single-layer NN.
Difficulty: Moderate.
Group: 4 students, should have good Python programming skills, knowledge of neural networks, PyTorch, and SciKit is helpful.
2 Pattern Space Segmentation & Pattern Classification with Multi-Layer Neural Network
Description: Design and develop a neural net based pattern classifier that can locate regions of an input image that contain an input pattern (e.g., a tractor or automobile). Conduct tests, analyze performance and document results.
Difficulty: Moderate.
Group: 4 students, should have good Python programming skills, knowledge of PyTorch and SciKit is helpful.
3 Pattern Space Segmentation & Pattern Classification with PARIS Algorithm
Description: Design and develop an implementation of the PARIS pattern recognition algorithm, that can locate regions of an input image that contain an input pattern (e.g., a tractor or automobile). Conduct tests, analyze performance and document results.
Difficulty: Moderate (instructor will provide algorithm).
Group: 4 students, should have good Python programming skills, knowledge of SciKit is helpful.
4 Cryptanalysis of Simple Ciphers (Caesar and Vigenere Ciphers)
Description: Design and develop software in C, C++, or Python programming languages to (1) analyze and break a Caesar cipher, then (2) analyze and break a Vigenère cipher, which is a series of interwoven Caesar ciphers. Conduct tests, analyze performance and document results.
Difficulty: Moderate to Difficult.
Group: 4 students, should have good Python programming skills, knowledge of SciKit is helpful.
5 Detection and Remediation of Security Vulnerabilities (in an Internet software application)
Description: Design and develop software in C, C++, or Python programming languages to (1) detect vulnerabilities in a Web application that you also develop, then (2) remediate those vulnerabilities, thus rendering your Web app secure. Conduct tests, analyze performance and document results.
Difficulty: Moderate.
Group: 4-5 students, should have good design and programming skills, knowledge of SciKit is helpful.
6 Blockchain Applications (Secure Financial Transaction, Secure Database Access)
Description: Design and develop software in C, C++, or Python programming languages to (a) support secure blockchain-based transactions --or-- (b) support secure blockchain-based database storage and retrieval. Conduct security tests, analyze performance and document results.
Difficulty: Moderate to difficult.
Group: 4 students, should have good design and programming skills, knowledge of SciKit is helpful.
Questions? Email the instructor: mssz@cise.ufl.edu