Papers

Title 1: Deep learning-based 3D printer fault detection
- Submitted (ICUFN 2021 - Accepted)

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

Last Week's Progress

[1] ICUFN 2021
- Gathered related works
- Modified and upgrading paper

[3] Summer Intensive
- Methodology
- Simulation

This Week Todo's

[1] ICUFN 2021
- Continue working on the paper
- Gather related works

[3] Summer Intensive
- Simulation
- Collecting data

Project Progress

3D Monitoring Project

Last Week's Project

1. Captured dataset
2. Labeled the data
3. Surveyed related works

This Week's Project

1. Work with the OctoPi
2. Gather dataset (OctoPi and Camere)
3. Survey and gather related works (fault prediction in general)

Monthly Goals

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 my paper (Sept)

Annual Goals

1. Publish two or three conference papers (Domestic and International)
- KICS Summer 2021 (done)
- ICUFN 2021 (done)

2. Publish at least one International Journal
- ICUFN 2021 Paper (ICT Express)
- Summer Intensive 2021