MNIST Handwritten Classification
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Machine Learning course project
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Machine Learning course project
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Machine Learning course project: Solve the adaptive echo calcellation problem, such that the noise is removed from music
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Master Thesis
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Machine Learning course project: Solve the adaptive echo calcellation problem, such that the noise is removed from music
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Time-series forecasting - A winning contribution to the Siemens’ Tech For Sustainability 2023 campaign in the Swarm Behaviour on the Grid track
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February 2020 ~ September 2021
This project was centered around PlantCV (Plant Computer Vision), an open-source software package meticulously designed for plant phenotyping analysis. Developed in Python and integrating advanced image processing libraries such as OpenCV (Open Source Computer Vision Library), PlantCV aims to provide plant scientists and researchers with a powerful, flexible, and user-friendly tool for automating and quantifying the extraction of plant phenotypic information from various image data.
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October 2021 ~ December 2021
This project focused on the application of Mask R-CNN, a state-of-the-art model for instance segmentation tasks, to detect and classify common types of cell nuclei in H&E (Hematoxylin and Eosin) stained pathology images of Non-Small Cell Lung Cancer (NSCLC) and Breast Cancer. By leveraging transfer learning and customizing the loss function of Mask R-CNN, the project aimed to address the challenges posed by incomplete labeling in the dataset and improve the model’s performance in both detection and classification tasks.
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September 2023 – October 2023
This project aimed to extend the capabilities of an existing in-house developed tool, OptiReader, designed for the automatic parsing of eyeglass prescriptions. Initially supporting the North American market, the project’s goal was to adapt the tool for the Japanese market, particularly for VR eyeglasses, by incorporating innovative document understanding technologies and custom solutions to handle unique prescription formats prevalent in Japan.
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May 2023
This project is actually a pre-interview project for data scientist. I have got a chance to perform data analysis and time-series modeling and forecasting.