
A Mining Frame Work of CO-PO Attainment using Deep Learning Techniques
Author(s) -
Pasquale Sena,
P. Sammulal,
Suresh Pabboju,
D. Krishna Reddy
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.d1015.0394s220
Subject(s) - frame (networking) , computer science , convolutional neural network , artificial intelligence , automation , deep learning , work (physics) , frame work , identification (biology) , machine learning , artificial neural network , engineering , mechanical engineering , architectural engineering , telecommunications , botany , biology
student performance measured in CO-PO (Course Outcome and Program Outcome) attainment for OMR based answer sheet automation playing very curtail role in pupil concert analysis in this approach. In the proposed work, marks evaluation sheet is consider as input image, then apply frame cropping technique to extract the marks filled table by subdividing into cells as individual images by frame cropping technique. In order to recognition of hand written digit in each frame, various machine learning models are adopted, trained. Experimental results from proposed work show that convolutional neural network excels higher in identification digits from frames. The outputs are then converted to CSV version, which is used to evaluate CO-PO attainment for each learner. The experiments have been conducted and tested in proposed work on various machine learning techniques and compared the results to pick the optimal model
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