Rate My Professor Fikree Hassan

Hassan's research interests lie in signal and image processing, with a particular emphasis on developing image enhancement and restoration algorithms and their applications in computer vision. His specific areas include Image Enhancement and Restoration, Computer Vision, Human Color Vision, and Signal Processing. He is accepting PhD students and supervises projects such as a new adaptive color cast removal algorithm for varying illumination conditions based on convolutional vision transformer methods. Key publications include "A Comparative Analysis of Deep Learning Models and Gradient Computation for Rally Detection in Badminton Videos" (SN Computer Science, 2025), "An integrated enhancement method to improve image visibility and remove color cast for sand-dust image" (Multimedia Tools and Applications, 2025), "An ℓ0 total generalized variation for impulse noise removal" (Multimedia Tools and Applications, 2025), "Conjugate Momentum Quadratic Penalty Alternating Minimization for Total Variation Image Restoration" (IEEE International Conference on Systems, Man, and Cybernetics, 2024), and "Service and End of Rally Detection in Badminton Videos" (International Conference on Sports Analytics, 2024). Additionally, he serves as a peer reviewer for prestigious journals such as Neurocomputing, Scientific Reports, and Journal of Imaging in 2024. Hassan has produced 23 research outputs to date.