Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches MM Rahaman, C Li, Y Yao, F Kulwa, MA Rahman, Q Wang, S Qi, F Kong, ... Journal of X-ray Science and Technology 28 (5), 821-839, 2020 | 355 | 2020 |
DeepCervix: A deep learning-based framework for the classification of cervical cells using hybrid deep feature fusion techniques MM Rahaman, C Li, Y Yao, F Kulwa, X Wu, X Li, Q Wang Computers in Biology and Medicine 136, 104649, 2021 | 217 | 2021 |
Breast cancer segmentation methods: current status and future potentials E Michael, H Ma, H Li, F Kulwa, J Li BioMed research international 2021 (1), 9962109, 2021 | 105 | 2021 |
A state-of-the-art survey for microorganism image segmentation methods and future potential F Kulwa, C Li, X Zhao, B Cai, N Xu, S Qi, S Chen, Y Teng Ieee Access 7, 100243-100269, 2019 | 79 | 2019 |
Gastric histopathology image segmentation using a hierarchical conditional random field C Sun, C Li, J Zhang, MM Rahaman, S Ai, H Chen, F Kulwa, Y Li, X Li, ... Biocybernetics and Biomedical Engineering 40 (4), 1535-1555, 2020 | 49 | 2020 |
A new pairwise deep learning feature for environmental microorganism image analysis K Frank, L Chen, Z Jinghua, S Kimiaki, K Sergey, Z Xin, J Tao, G Marcin Environmental Science and Pollution Research, 2022 | 48 | 2022 |
An enhanced framework of generative adversarial networks (EF-GANs) for environmental microorganism image augmentation with limited rotation-invariant training data H Xu, C Li, MM Rahaman, Y Yao, Z Li, J Zhang, F Kulwa, X Zhao, S Qi, ... IEEE Access 8, 187455-187469, 2020 | 41 | 2020 |
A review of clustering methods in microorganism image analysis C Li, F Kulwa, J Zhang, Z Li, H Xu, X Zhao Information technology in biomedicine, 13-25, 2021 | 36 | 2021 |
A Multiscale CNN‐CRF Framework for Environmental Microorganism Image Segmentation J Zhang, C Li, F Kulwa, X Zhao, C Sun, Z Li, T Jiang, H Li, S Qi BioMed Research International 2020 (1), 4621403, 2020 | 26 | 2020 |
EMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks Z Li, C Li, Y Yao, J Zhang, MM Rahaman, H Xu, F Kulwa, B Lu, X Zhu, ... Plos one 16 (5), e0250631, 2021 | 19 | 2021 |
A SARS-CoV-2 microscopic image dataset with ground truth images and visual features C Li, J Zhang, F Kulwa, S Qi, Z Qi Chinese conference on pattern recognition and computer vision (PRCV), 244-255, 2020 | 19 | 2020 |
Segmentation of Weakly Visible Environmental Microorganism Images Using Pair-wise Deep Learning Features F Kulwa, C Li, M Grzegorzek, MM Rahaman, K Shirahama, S Kosov Biomedical Signal Processing and Control, Accepted for publication, 2022 | 13 | 2022 |
Hierarchical conditional random field model for multi‐object segmentation in gastric histopathology images C Sun, C Li, J Zhang, F Kulwa, X Li Electronics Letters 56 (15), 750-753, 2020 | 13 | 2020 |
Foldover features for dynamic object behaviour description in microscopic videos X Li, C Li, F Kulwa, MM Rahaman, W Zhao, X Wang, D Xue, Y Yao, ... IEEE Access 8, 114519-114540, 2020 | 12 | 2020 |
Fanjie Kong, Xuemin Zhu, and Xin Zhao. Identification of covid-19 samples from chest x-ray images using deep learning: A comparison of transfer learning approaches MM Rahaman, C Li, Y Yao, F Kulwa, MA Rahman, Q Wang, S Qi Journal of X-ray Science and Technology 28 (5), 821-839, 2020 | 11 | 2020 |
MRFU-Net: a multiple receptive field u-net for environmental microorganism image segmentation C Li, J Zhang, X Zhao, F Kulwa, Z Li, H Xu, H Li Information technology in biomedicine, 27-40, 2020 | 9 | 2020 |
Analyzing the impact of varied window hyper-parameters on deep CNN for sEMG based motion intent classification F Kulwa, OW Samuel, MG Asogbon, OO Obe, G Li 2022 IEEE International Workshop on Metrology for Industry 4.0 & IoT …, 2022 | 8 | 2022 |
Information technology in biomedicine C Li, J Zhang, X Zhao, F Kulwa, Z Li, H Xu, H Li Cham: Springer, 13-25, 2020 | 8 | 2020 |
A Multi-Dataset Characterization of Window-based Hyper-parameters for Deep CNN-driven sEMG Pattern Recognition K Frank, Z Haoshi, S Oluwarotimi, G Mojisola, S Erik, K Rami, ... IEEE Transactions on Human-Machine Systems, 2023 | 5 | 2023 |
Inspection of EEG signals for noninvasive blood glucose monitoring in prediabetes diagnosis T Igbe, OW Samuel, J Li, F Kulwa, A Kandwal, Z Nie 2023 IEEE International Symposium on Medical Measurements and Applications …, 2023 | 4 | 2023 |