Milad Mirjalili
Milad Mirjalili is a Master's graduate student in Electrical Engineering at KNT University of Technology in Tehran, Iran. He specializes in various aspects of machine vision, machine learning, deep learning, and image and video processing. His research focuses on the development of advanced algorithms in the field of computer vision. For example, he developed an algorithm for motion estimation Video and text detection GitHub using Python.
Research Interests
- Machine Vision: Motion analysis, video compression, object recognition, and action recognition
- Machine learning: Supervised/ unsupervised learning, and reinforcement learning
- Deep learning: Convolutional neural networks, generative AI
- Image and Video processing
- Microcontroller programming
Master Thesis
Developing a Variable-Size Adaptive Block Matching Motion Estimation Algorithm
Milad's master thesis focuses on creating a variable-size adaptive block matching motion estimation algorithm, which aims to enhance the accuracy and efficiency of motion estimation in video processing applications. He also presented a deep learning method to enhance the block matching motion estimation algorithm.
Computer Skills
Milad Mirjalili is proficient in programming languages such as Python, C, and Java. He has extensive experience with libraries, including OpenCV, Pandas, TensorFlow, scikit-learn, NumPy, Matplotlib, and SciPy. Additionally, he is skilled in using Android Studio for Android software development and Unity Engine for game development.