I'm a graduate of YCC's Class of 2020 and majoring in Information, Science and Technology (IST). My interests include software development, artificial intelligence, machine learning, deep learning, computer vision, and natural language processing.
I'm passionate to solve current problems of the society with the help of machine learning and deep learning algorithms. I am always looking to learn more.
Take a look at some of the things I love working on.
I like to research and develop object detection, image segmentation, and image recognition technologies.
I have worked as the NLP research fellow at Myanmar Natural Language Processing Lab and experience with data preparing and NLP methodologies.
I love the mathematic and theory to build, training and deploying models.
I have research experience using deep learning algorithms such as CNN. I have experience using Tensorflow, PyTorch, and Keras.
Optical Character Recognition (OCR) is a process of converting an image, such as handwritten files, scanned document or electronic fax, into machine-editable format. The system is to convert the data available on printed papers written in Myanmar language into computer editable documents. This work includes image pre-processing (to improve image quality), segmentation (to extract each character), and recognition(to recognize each character by CNN).
Cyanobacteria is one of bio indicators of water quality. The project is automatically identifying planktons in water. The project also aims at incorporating computer science and artificial intelligent (AI) into the environmental monitoring and analysis practices. It includes such tasks:
-Creating a dataset of cyanobacteria images for seven classes of cyanobacteria.
-Building machine learning models based on the above dataset.
-Deploy the model to a web app on the google app engine
Insects cause damage to crops and mainly affect the productivity of crop yield. Classification of insects is a difficult task due to the complex structure and having a high degree of similarity of the appearance between distinct species. This project is to recognize and classify insects in the crops at an early stage, especially to prevent the spread of insects, which cause crop diseases by selecting effective pesticides and biological control methods.