Computer Vision Deep Learning

,

Bùi Đức Anh

** *** *** **., **** Hoa, Di An, Binh Duong ***.*********@*****.***.** +84-33-946-**** OBJECTIVE

As a recent graduate, I am deeply passionate about artificial intelligence, particularly in the field of computer vision. Through- out my studies, I developed a strong interest in how computer vision technologies can be leveraged to address real-world challenges. I am eager to apply my skills and knowledge to contribute to innovative and impactful projects, aiming to make a tangible difference in industries such as healthcare, environmental conservation, and autonomous systems. EDUCATION

Ho Chi Minh city University of Technology (HCMUT) Oct.2021 - May.2025 Candidate for Bachelor of Computer Engieneering:

− Concentration in Embedded system and Machine learning, Computer vision.

− GPA: 7.14/10.

Ho Chi Minh city University of Technology (HCMUT) Class of 2026 Candidate for Master of Computer Science

EXPERIENCE

Renesas Design Vietnam Jun.2024 − Aug.2024

Intern

Technology On World (link) Nov.2024 − Present

Research

− Fine-tuned YOLOv8/YOLOv11 models to detect, segment specialized classes of wild animals(zebra, elephant, giraffe).

− Leveraged SAHI and SAM2 for Accelerating and Semi-Automating the Annotation Process in High-Resolution Real-World Datasets from the African Savanna(link) using X-anyLabeling Tool for enhanced labeling and efficiency.

− Conducted evaluation of dense (e.g., RAFT) and sparse (e.g., Lucas-Kanade) optical flow algorithms on high-resolution image datasets to benchmark performance and scalability.

− Tasked with researching and developing a lightweight and efficient model for real-time wildlife tracking on unmanned aerial vehicles (UAVs).

PROJECTS

Vietnamese Sentiment Analysis Mar−May.2025

Github: https://github.com/deadlyflourish4/modern_approach_nlp.git

− Designed and implemented a robust solution for text classification using deep learning models.

− Applied CNN, LSTM, and hybrid deep learning architectures for sentiment analysis on Vietnamese text data.

− Fine-tuned the pre-trained PhoBERT model to improve classification performance on domain-specific sentiment datasets. Simple autonomous-driving car Aug−Dec. 2023

Team leader, programmer. Github: https://github.com/luuxifer/CO3091-DA_TKLL.git

− Developing an end-to-end system using ROS (Robot Operating System) and Gazebo for simulation, integrating lane- following vehicle capabilities.

− Implemented advanced image processing algorithms, including bird’s-eye view lane detection and YOLOv3 for traffic sign detection, directly integrated with the camera system for enhanced accuracy.

− Optimized system performance by leveraging ROS’s modular architecture and integrating Linux-based solutions. Vietnam Weather Forecast

Mar−May.

2025

Github: https://github.com/deadlyflourish4/weather_focast_app.git

− Built a machine learning-based weather forecast system for Vietnam using FastAPI, XGBoost, and MongoDB.

− Integrated WorldWeatherOnline API for automated daily data fetching and model retraining via APScheduler.

− Enabled manual/automated retraining with configurable hyperparameters via RESTful endpoints.

− Deployed and validated the pipeline using Docker and exposed interactive Swagger UI for API access. Real-time Image Super Resolution on Embedded System with Deep Learning Approach Aug.2024−May.

2025

Github: https://github.com/deadlyflourish4/super-resolution-lw.git

− Applied knowledge distillation, quantization to develop a lightweight model for image super-resolution.

− Optimized model performance by converting it to ONNX and deploying with TensorRT, achieving approximately 2.5 faster inference.

− Conducted experiments on NVIDIA Jetson Nano B01 for edge deployment validation. HONORS & AWARDS

BOSCH CODERACE CHALLENGE 2023 - EXCEED THE LIMITLESS MIND(cert) May−Jul. 2023

- Top 5 in Final round of Bosch Coderace Challenge 2023. SKILLS

Programming languages: C/C++, Python, JavaScript.

Frameworks/Libraries: Pytorch, OpenCV, Tensorflow, ONNX, TensorRT. Operating System: Linux, Bash scripts.

Tools: Github, Docker, Kubernets(basic).

Hardwares: NVIDIA Jetson, ...

LANGUAGE

English: IELTS 6.0.

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