I have worked at ...
Chromasens GmbH (Germany)
6.2021 - 8.2021
Machine Vision Research Intern (Summer Internship)
Emage Development - Emage Group (Vietnam)
1.2019 - 5.2020
AI Engineer (Full-time)
I Have Studied My ...
- First semester
- Second semester
- Third semester - Fourth semester
- Two-year scientific Erasmus+ Joint Master’s Degree, aiming to train the next generation of highly-skilled industrial experts in applied colour science, in various cutting-edge industries (photonics, optics, spectral imaging, multimedia technologies, computer graphics and vision) in a diverse range of sectors (including multimedia, health care, cosmetic, automotive, agro-food). The two areas of focus are spectral technologies and applied colour imaging.
- GPA: 3.2/4 (Currently).
- Master Thesis: Visualization Solutions For Intraoperative Hyperespectral Imaging (on-going).
- GPA: 3.2/4.
- Bachelor thesis: A real-time unlocking door system by face recognition using Deep Learning.
I have Done ...
Semantic Segmentation For Human Placenta Tissue Hyperspectral Images
In this project, I leveraged the backbone of HRNet Architecture to implement a DL model for human placeta tissue (hyperspectral image dataset) segmentation. I trained the model with two options: 38 wavelength bands of spectral images and 3 bandes of spectral images after applying PCA. I evaluated the model with various metrics: mIoU, Accuracy, Precision and Recall. The mIoU score of the trained model is 89% on the test dataset.
Domain Adaptation and Image Dehazing on Nighttime Hazy Image
In this project, me, David and Milan, who are my teammates, performed a domain adaptation module to dehaze nighttime hazy images. Milan developed a state-of-the-art GASDA algorithm to train on real and hazy images in order to obtain the depth of images, I implemented the CycleGAN to train domain adaption on our dataset (synthetic and real images) and David managed to write scripts for collecting real nighttime hazy images and implement different metrics for model evaluation such as MSE, PSNR, SSIM, CIEDE2000, BRISQUE, FADE. Our result outperformed existing state-of-the-art approaches in term of real nighttime image dehazing but the result for nighttime synthetic image dehazing was not good and needed for further research.
A Literature Review And Implementation of Several Clustering Techniques on MoCap Hand Postures Dataset
In this project, I presented and analyzed the mathematical background of two different clustering algorithms: K-Means, Agglomerative algorithms. I implemented these approaches on Google Colab to conduct experiments with the MoCap Hand Postures Dataset from the Center for Machine Learning and Intelligent Systems from the University of California, Irvine. For model evaluation, I developed and compared various metrics such as Homogeneity, Completeness, V_measure, Fowlkes_Mallows, Silhouette, Hungarian Error, Entropy, Gini Coefficient . Addtionally, I also implemented SVM, K-NN, Decision Tree Classifier and CNN-based approach to compare the difference between clustering and classificaiton problems.
Pose Estimation and Tracking of Pigs (On-going to be publishable)
In this project, me and Milan, who is my teammate, modified OpenPose algorithms to work with the dataset of Pig. We replaced the backbone by the EfficientNet architecture along with spatial attention mechanism to extract features. The result was evaluated on AP_OKS and AR_OKS and the best feature-extractor backbone was selected. This project is under writing for academic conference submission.
A Literature Review of Top-down approaches on human pose estimation (On-going to be publishable)
In this project, I reviewed 22 papers on the topic top-down approahces on human pose estimation. I deeply discussed about the mathematical background of each method and summarized shortly in order to provide newcomers an extensive review of deep learning methodsbased 2D images for recognizing the pose of people. The papers, taken into account, were between 2016 and 2020.
I have gained skills in ...
Technical skills(s)
- Programming Languages: Python, C++, C#, WPF, Halcon, R, git, Multi-thread programming, HTML/CSS.
- Technical Softwares/Frameworks: OpenCV, Numpy, Tensorflow, Keras, Scikit-Learn, PyQt5, LaTex, Pandas, Visual Studio, MATLAB.
Language(s)
- Vietnamese (Native speaker).
- English (IELTS 6.5 - Fluent for working).
- Chinese (Basic communication)
Design and photography
- Photoshop
- Illustrator
- Lighroom
- Photography skills
My achievements are ...
- Erasmus Mundus Traineeship Grant for summer internship at Chromasens, Germany. (2021)
- Erasmus Mundus Mobility Grant for 2nd semester of Master program taking place in France. (2021)
- COSI representative student – cohort 2020-2022. (2020)
- Consortium Scholarship (9000€ fee-waiver) in Computational Colour and Spectral Imaging (COSI) in Norway, France and Finland. (2020)
- Speaker at What Works conference for “Boosting ASEAN student mobility” organized by SHARE in Phnom Penh, Cambodia. (2018)
- Representative student giving a speech at ASEAN University Network – Quality Assurance (AUN – QA) Assessment Ceremony for recognizing 4 programs at HCM, University of Technology and Education. (2018)
- SHARE fully-funded scholarship for one semester exchange at University College Cork, Ireland. (2017)
Contact Me At ...