Alaa AlZoubi
Name | Alaa AlZoubi |
---|---|
Job title | Senior Lecturer in Computer Science |
Research institute | College of Science and Engineering |
ORCID | https://orcid.org/0000-0003-1167-170X |
Research outputs
Explainable DCNN Decision Framework for Breast Lesion Classification from Ultrasound Images Based on Cancer Characteristics
AlZoubi, A., Eskandari, A., Yu, H. and Du, H. 2024. Explainable DCNN Decision Framework for Breast Lesion Classification from Ultrasound Images Based on Cancer Characteristics . Bioengineering. 11 (5), pp. 1-23. https://doi.org/10.3390/bioengineering11050453ENAS-B: Combining ENAS with Bayesian Optimisation for Automatic Design of Optimal CNN Architectures for Breast Lesion Classification from Ultrasound Images
Ahmed, M., Du, H. and AlZoubi, A. 2023. ENAS-B: Combining ENAS with Bayesian Optimisation for Automatic Design of Optimal CNN Architectures for Breast Lesion Classification from Ultrasound Images. Ultrasonic Imaging. https://doi.org/10.1177/01617346231208709Automatic Detection of Thyroid Nodule Characteristics From 2D Ultrasound Images
Han, D., Ibrahim, N., Lu, F., Zhu, Y., Du, H. and AlZoubi, A. 2023. Automatic Detection of Thyroid Nodule Characteristics From 2D Ultrasound Images. Ultrasonic Imaging. pp. 1-18. https://doi.org/10.1177/01617346231200804Automatic Bi-LSTM Architecture Search Using Bayesian Optimisation for Vehicle Activity Recognition
AlZoubi, A. and Radhakrishnan , R. 2023. Automatic Bi-LSTM Architecture Search Using Bayesian Optimisation for Vehicle Activity Recognition. in: A. Augusto de Sousa, Kurt Debattista, Alexis Paljic, Mounia Ziat, Christophe Hurter, Helen Purchase, Giovanni Maria Farinella, Petia Radeva and Kadi Bouatouch (ed.) Computer Vision, Imaging and Computer Graphics Theory and Applications New York Springer. pp. 108–134Classification of breast lesions in ultrasound images using deep convolutional neural networks: transfer learning versus automatic architecture design
AlZoubi, A., Lu, F., Zhu, Y., Ying, T., Ahmed, M. and Du, H. 2023. Classification of breast lesions in ultrasound images using deep convolutional neural networks: transfer learning versus automatic architecture design. Medical & Biological Engineering & Computing. pp. 1-15. https://doi.org/10.1007/s11517-023-02922-yMachine Learning Assisted Doppler Features for Enhancing Thyroid Cancer Diagnosis
Zhu, Y., Du, H., Jiang, Q., Zhang, T., Huang, X., Zhang, Y., Shi, X., Shan, J. and AlZoubi, A. 2021. Machine Learning Assisted Doppler Features for Enhancing Thyroid Cancer Diagnosis. Journal of Ultrasound in Medicine. 41 (8), pp. 1961-1974. https://doi.org/10.1002/jum.15873A generic deep learning framework to classify thyroid and breast lesions in ultrasound images
Zhu, Y.C., AlZoubi, A., Jassim, S., Jiang, Q., Zhang, Y., Wang, Y.B., Ye, X.D. and Hongbo, D.U. 2021. A generic deep learning framework to classify thyroid and breast lesions in ultrasound images. Ultrasonics. 110, pp. 1-8. https://doi.org/10.1016/j.ultras.2020.106300170
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