A comprehensive review of few-shot action recognition
Few-shot action recognition aims to address the high cost and impracticality of manually
labeling complex and variable video data in action recognition. It requires accurately …
labeling complex and variable video data in action recognition. It requires accurately …
Evaluating approaches of training a generative large language model for multi-label classification of unstructured electronic health records
Multi-label classification of unstructured electronic health records (EHR) is challenging due
to the semantic complexity of textual data. Identifying the most effective machine learning …
to the semantic complexity of textual data. Identifying the most effective machine learning …
[CITATION][C] Towards Generalizable Deep Learning-Based Human Action Recognition
K Peng - 2024