Conferences
Sagor, M. K., Dipto, S. M., Jahan, I., Chowdhury, S., Reza, M. T., & Alam, M. A. (2021, December 8). An efficient deep learning approach for detecting lung disease from chest X-Ray images using transfer learning and ensemble modeling. 2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE). https://doi.org/10.1109/CSDE53843.2021.9718454
Sadat, S. U., Shomee, H. H., Awwal, A., Amin, S. N., Reza, M. T., & Parvez, M. Z. (2021). Alzheimer’s disease detection and classification using transfer learning technique and ensemble on convolutional neural networks. 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 1478–1481. https://doi.org/10.1109/SMC52423.2021.9659179
Reza, M. T., Ahmed, F., Sharar, S., & Rasel, A. A. (2021, September 16). Interpretable retinal disease classification from OCT images using deep neural network and explainable AI. 2021 International Conference on Electronics, Communications and Information Technology (ICECIT). https://doi.org/10.1109/ICECIT54077.2021.9641066
Tafannum, F., Sharear Shopnil, M. N., Salsabil, A., Ahmed, N., Rabiul Alam, M. G., & Reza, M. T. (2021). Demystifying black-box learning models of rumor detection from social media posts. In P. R. (Ed.), 2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) (pp. 358–364). IEEE. https://doi.org/10.1109/UEMCON53757.2021.9666567
Reza, M. T., Zaman, M. S., Mobin, I., & Alam, M. A. (2019). Analysis and 3D representation of visual information from fMRI of ventral temporal cortex using neural network and support vector machine. 5th International Conference on Advances in Electrical Engineering, ICAEE 2019, 207–211. https://doi.org/10.1109/ICAEE48663.2019.8975656
Reza, M. T., Mehedi, N., Tasneem, N. A., & Ashraful Alam, M. (2019, December 18). Identification of crop consuming insect pest from visual imagery using transfer learning and data augmentation on deep neural network. 2019 22nd International Conference on Computer and Information Technology (ICCIT). https://doi.org/10.1109/ICCIT48885.2019.9038450