| 1 |
Farukuzzaman Faruk |
VGGCovidNet: A Deep Convolutional Neural Network to Predict COVID-19 Cases from X-Ray Images |
IEEE |
2021 |
Conference |
| 2 |
Farukuzzaman Faruk |
RGU-Net: Residual Guided U-Net Architecture for Automated Segmentation of COVID-19 Anomalies Using CT Images |
IEEE |
2021 |
Conference |
| 3 |
Md. Farukuzzaman Faruk |
ResidualCovid-Net: An Interpretable Deep Network to Screen COVID-19 Utilizing Chest CT Images |
IEEE |
2021 |
Conference |
| 4 |
Mrinmoy Mondal; Md. Farukuzzaman Faruk; Nasif Raihan; Protiva Ahammed |
Deep Transfer Learning Based Multi-Class Brain Tumors Classification Using MRI Images |
IEEE |
2021 |
Conference |
| 5 |
Md. Ahsan Habib Raj , Md. Al Mamun & Md. Farukuzzaman Faruk |
CNN Based Diabetic Retinopathy Status Prediction Using Fundus Images |
IEEE |
2020 |
Conference |
| 6 |
Abu Sayeed, Abdul Alim, Ali Hossain & Md. Farukuzzaman Faruk |
Target Class Oriented Subspace Detection for Hyperspectral Image Classification by Using Mutual Information and Cross Cumulative Residual Entropy |
IEEE |
2020 |
Conference |
| 7 |
Md. Farukuzzaman Faruk and Abu Sayeed |
K-mer Based DNA Methylation Status Prediction Using Support Vector Machine |
IEEE |
2019 |
Conference |
