Title 1: Deep learning-based 3D printer fault detection
- Submitted to ICUFN
Title 2: An inference time-efficient 3D printer fault detection using CNN
- Submitted (KICS 2021 - Accepted)
Title 3: Edge AI-based 3D Printer Monitoring and Fault Prediction
- Summer Intensive 2021
Title 4: Dataset Anomalies
[1] ICUFN 2021
- Accepted
- Improved for possible journal paper
[3] Summer Intensive
- Introduction
- Presented my idea
[1] ICUFN 2021
- Response to the comment from the reviewers
- Continue revising and improve the paper
- Finish camera-ready and register
[2] Summer Intensive
- Continue writing introduction
- Survey Raspberry Pi monitoring
- Data collection
[4]
- Collect dataset
- Study-related works
3D Monitoring Project
1. Explore Octoprint and Cura
2. Survey fault prediction in general
1. Apply OctoPrint and Cura on the 3D printer
2. Collect dataset
3. Study image processing
1. Journal paper
- Search and review related works
- Compare conventional and machine learning methods
2. Learn more about machine learning and deep learning with Python
- Study for online tutorials
- Read articles
- Re-simulate what I learn
3. Summer Intensive 2021
- Finish half of the paper
- Introduction
- related work
1. Publish two or three conference papers (Domestic and International)
- KICS Summer 2021 (done)
- ICUFN 2021 (accepted)
2. Publish at least one International Journal