基于卷积神经网络的 MCQ 评估附matlab代码.zip

Copyright (c) 2018 Mahmoud Afifi Assiut University - York University The source code is provided here for reasonable academic fair use. For commercial use of either the source code or the dataset, please contact us: m.afifi@aun.edu.eg - mafifi@eecs.yorku.ca Please cite the following paper, if you are going to use this software: Mahmoud Afifi and Khaled F. Hussain, �The Achievement of Higher Flexibility in Multiple Choice-based Tests Using Image Classification Techniques", International Journal on Document Analysis and Recognition (IJDAR), 2019. For more information, visit the project webpage: https://sites.google.com/view/mcq-dataset Requirements: Before starting, please download the following files: 1- BoW model (straight-forward): https://drive.google.com/open?id=1fxzYGTwdhgo6zBgqvP788FCCGEVKny_P 2- BoW model (stage 1): https://drive.google.com/open?id=1kfshZDQ5A22pBJZ4_8dp7XkNaKY94tVo 3- BoW model (stage 2): https://drive.google.com/open?id=1E8bTjftB3W-TQKcivmI56yjlAW-uZ7_s 4- CNN model (straight-forward): https://drive.google.com/open?id=1FFL3cC9pw6mSPCB_VB2Q8aApyiHOIaH0 5- CNN model (stage 1): https://drive.google.com/open?id=1x33SwGsedmcNmWxE0YR1_WDqit4Qp5BB 6- CNN model (stage 2): https://drive.google.com/open?id=1FrCUrbe78Gmp5CfzQ1Vaw4j2UrqtT6cX Locate all the downloaded files in the same folder of ReadMe.txt file. To start, run main.m Citation: Mahmoud Afifi and Khaled F. Hussain, �The Achievement of Higher Flexibility in Multiple Choice-based Tests Using Image Classification Techniques", International Journal on Document Analysis and Recognition (IJDAR), 2019.