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Effect of Neural Network on Reduction of Noise for Edge Detection
Get PDFProcessing photographic images is important in many applications, among them the development of automated driver assistance systems (ADAS) and autonomous vehicles. Many techniques are used for processing images, including neural networks, other types of machine learning, and edge detection. One common issue with processing these photos is the presence of noise, whether caused by the camera itself or by physical conditions (e.g., weather conditions or dirt on road signs). In this paper, a neural network is used for noise reduction to improve edge detection results and tested with two kinds of noise, Gaussian and salt & pepper noise, and three different edge detection algorithms, Canny, Sobel, and Zhang. Results showed that the noise reduction process was effective in improving performance of the edge detection process, with the exception of conditions where the noise was originally very minimal
2/24/2021: Faculty Senate Unapproved Meeting Minutes
No full textFaculty Handbook Change Second Reading of Thesis Committee Changes - Approved with amendment (12,0,0) Amendment to Thesis Committee Changes - Remove last sentence of 3.1.1.3 - Approved (7,6,0)
UCC Changes Program Change: Addition of Engineering Management Concentration to BSE - Approved (12,1,0)
Motion Move to postpone indefinitely Motion 3: The Faculty Senate requests that a policy be developed for the permission of use of employees likenesses in university materials, including promotional materials. - Approved (11,2,0
3/24/2021: Faculty Senate Unapproved Meeting Minutes
No full textUCC Changes Course Change: CE 695 change from Pass/Fail to Satisfactory/Unsatisfactory - Approved (13,0,0) New Program: Masters of Engineering Program with all affiliated concentrations and courses - Approved (10,3,1
Winter 2021: Data Analytics
No full textThis course is a required core course in the modified Applied Data Science and Data Analytics graduate program. In addition, the course can be used for meeting the requirements for undergraduate and graduate concentrations in Business Analytics/Data Analytics. We expect that subsequent versions of this course can also be targeted at a corporate audience