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Dr. Ayesha Saadia
Assistant Professor
Contact Information
  [email protected]
  687 and Google Citation

Education Detail
PhD (Software Engineering) NUST, Pakistan
MS (Computer Science) VU, Pakistan
BS (Computer Science) VU, Pakistan

1. Hassan, M., Ali, S., Kim, J.Y., Saadia, A., Sanaullah, M., Alquhayz, H. and Safdar, K., 2023. Developing a Novel Methodology by Integrating Deep Learning and HMM for Segmentation of Retinal Blood Vessels in Fundus Images. Interdisciplinary Sciences: Computational Life Sciences, pp.1-20.2. Murtza, I., Saadia, A., Basri, R., Imran, A., Almuhaimeed, A. and Alzahrani, A., 2022. Forex Investment Optimization Using Instantaneous Stochastic Gradient Ascent—Formulation of an Adaptive Machine Learning Approach. Sustainability, 14(22), p.15328.3. AlEisa, H.N., Touiti, W., Ali ALHussan, A., Ben Aoun, N., Ejbali, R., Zaied, M. and Saadia, A., 2022. Breast Cancer Classification Using FCN and Beta Wavelet Autoencoder. Computational Intelligence and Neuroscience, 2022.4. Saadia, A. et al., 2018. A speckle noise removal method. Circuits, Systems, and Signal Processing, 37, pp.2639-2650.5. Saadia, A. et al., 2018. Incorporating fractional calculus in echo-cardiographic image denoising. Computers & Electrical Engineering, 67, pp.134-144.6. Saadia, A. et al., 2016. Fractional order integration and fuzzy logic based filter for denoising of echocardiographic image. Computer methods and programs in biomedicine, 137, pp.65-75.Conference Publications1. Saadia, A. et al., 2018, May. Image denoising method by endorsement of neighborhood pixels. In 2018 4th International Conference on Computer and Technology Applications (ICCTA) (pp. 175-178). IEEE.2. Saadia, A. et al, 2016, August. Echocardiography image enhancement using adaptive fractional order derivatives. In 2016 IEEE International Conference on Signal and Image Processing (ICSIP) (pp. 166-169). IEEE.

Research Interest
Medical Image Processing
Document Analysis
Deep Learning
Remote Sensing
Pattern Recognition
Machine and Deep Learning