MCQ assessment using image classification (CNN/BoVW)
Versión 1.0.0.2 (7,13 MB) por
Mahmoud Afifi
Flexible MCQ assessment system that handles crossed out answers
Matlab GUI implementation of the paper "The Achievement of Higher Flexibility in Multiple Choice-based Tests Using Image Classification Techniques".
The source code is provided here for reasonable academic fair use.
More information is provided in the readme file.
If you use this source code, please cite the following paper:
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.
Compatibilidad con la versión de MATLAB
Se creó con
R2016b
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS LinuxCategorías
- Image Processing and Computer Vision > Computer Vision Toolbox > Feature Detection and Extraction >
- Image Processing and Computer Vision > Image Processing Toolbox > Image Segmentation and Analysis > Image Quality >
- Image Processing and Computer Vision > Image Processing Toolbox > Image Filtering and Enhancement > Watermarking >
Más información sobre Feature Detection and Extraction en Help Center y MATLAB Answers.
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