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)
Title 3: Deep learning-based fault prediction
Title 4: Dataset Anomalies
Title 1:
- Improved my paper to submit in a journal paper
Title 3:
- Surveyed related papers
Title 4:
- Surveyed related papers
[1] ICUFN 2021
- Await for the result (July 15)
- Continue editing and submit to a journal paper
[3] Summer Intensive 2021
- Continue writing introduction
- Search related works
- Prepare ppt for summer intensive
[4] Dataset Collection
- Resume when the 3D printer is available
3D Monitoring Project
1. Meeting with the group
2. Searched and study-related works for 3D controller
1. Explore OctoPi
2. Collect data from the 3D
3. Study fault prediction in general
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)
2. Publish at least one International Journal