intern:vitransformer

Reviewed seminal papers on attention mechanisms, including:
- Attention Is All You Need
- Masked-attention Mask Transformer for Universal Image Segmentation
Developed proficiency in Anaconda and Python programming for AI applications.
Joined laboratory research under mentorship of senior researchers.

Supported experiments for the paper TGMformer: Transferability Guided Mask Transformer for Segmentation Domain Adaptation (led by senior Zhang Enming):
- Implemented baseline models comparing fine-tuning strategies (last layer vs. full network) for transfer learning.
- Formalized mathematical definitions for transfer learning, clustering algorithms, and attention masking in the Methods section.
- Assisted with LaTeX typesetting and document formatting.

Continued working on the paper TGMformer: Transferability Guided Mask Transformer for Segmentation Domain Adaptation
Engineered a data loader and task-splitting module for the ImageNet-R dataset to support experiments with the Hypernet framework.
Debugged and optimized code to improve functional reliability.

Evaluated experimental results from the Hypernet project and documented insights.
Authored a reflective summary highlighting growth in research skills, data processing, and software testing.