Short Biography
Mostafa Amin-Naji (in Persian: مصطفی امین ناجی) is currently working on SUper-Resolution ultrasound imaging using the Erythrocytes (SURE). He is working under the supervision of Prof. Jørgen Arendt Jensen at the Center for Fast Ultrasound Imaging (CFU), Technical University of Denmark (DTU). He received his MSc and BSc degrees in Electrical & Computer Engineering-Communication Systems from the Babol Noshirvani University of Technology in 2015 and 2018, respectively. The main areas of research that he is interested in are Computer Vision, Deep/Machine Learning, Image/Video/Signal Processing, Medical Image/Signal Analysis, Ultrasound Imaging, and Information Fusion. The title of his award-winning MSc thesis is “Image Fusion using Deep Learning”, for which he received the 2017-2018 best thesis prize from the Iranian Society of Machine Vision and Image Processing (ISMVIP). Additionally, his BSc thesis is entitled “New Multi-Focus Image Fusion Methods in Discrete Cosine Transform”, which was awarded Outstanding IEEE BSc thesis in IEEE Iran Section Award in 2015-2016. A total of 18 peer-reviewed publications have been accepted from his BSc, MSc, and other projects, as well as some papers that are in the process of being completed. He has extensive experience in programming languages, including Python (libraries of PyTorch, TensorFlow, OpenCV, etc.) and Matlab. He is a reviewer in ISI Journals of Information Fusion-Elsevier, Pattern Recognition-Elsevier, Neurocomputing-Elsevier, IEEE Transactions on Computational Imaging-IEEE, IEEE Access-IEEE, IET Image Processing, IET Digital Library; Multidimensional Systems and Signal Processing, Springer.
My Papers Code
Multi-Focus Image Fusion in DCT Domain using Variance and Energy of Laplacian and Correlation Coefficient for Visual Sensor Networks
Multi-focus image fusion using Singular Value Decomposition in DCT domain
A new multi-focus image fusion technique based on variance in DCT domain Matlab Code
