Finalist in Global AI Week Hackathon (Upstage AI Hackathon).

• Objective: Develop an AI-driven chatbot to assist with supplement and medication intake.
• Approach:
  • Designed and implemented chatbot functionality using LLMs, Langchain, RAG, and Gradio.
  • Optimized responses through retrieval-augmented generation (RAG).

1st place winner at Smilegate FutureLab AI Service Weeklython.

• Objective: Create an AI-based game scenario generator for dynamic content creation.
• Approach:
  • Applied GPT fine-tuning, prompt engineering, and DALL·E.
  • Developed an interactive UI using Gradio.

한글:

• yolo-v5를 활용한 object detection 모델 개발 및 Jetson-Nano를 이용한 판별 시스템 구축

  • local 환경에서 이물질을 판별할 수 있도록 dataset 구성 및 yolo-v5 baseline model fine-tuning 진행.
  • Jetson-Nano에서 사용할 수 있도록 경량화 진행.
  • 95%의 정확도로 이물질 검출 성능 입증.
  • KSME2022 포스터 발표.

English:

• Developed an object detection model using YOLOv5 and built a classification system using Jetson Nano.
  • Constructed a dataset for detecting foreign substances in a local environment and fine-tuned a YOLOv5 baseline model.
• Optimized the model for deployment on Jetson Nano by applying model compression techniques.
• Achieved 95% accuracy in detecting foreign substances.
• Presented a poster at KSME2022 (The Korean Society of Mechanical Engineers).

Tech Stack

• YOLOv5
• Jetson Nano
• Python
• CUDA
• OpenCV
• PyTorch