Chenyu Zhu

ORCID: 0009-0000-6240-9985
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About
Contact & Profiles
Research Areas
  • Video Surveillance and Tracking Methods
  • Optical Systems and Laser Technology
  • Hand Gesture Recognition Systems
  • Topic Modeling
  • Advanced Image Fusion Techniques
  • Natural Language Processing Techniques
  • Human Pose and Action Recognition
  • Advanced Measurement and Detection Methods
  • Remote Sensing and Land Use

Hangzhou Normal University
2025

Soochow University
2024

Nanjing University of Science and Technology
2024

Multi-aspect controllable text generation aims to control in attributes from multiple aspects, making it a complex but powerful task natural language processing. Supervised fine-tuning methods are often employed for this due their simplicity and effectiveness. However, they still have some limitations: low rank adaptation (LoRA) only fine-tunes few parameters has suboptimal effects, while full (FFT) requires significant computational resources is susceptible overfitting, particularly when...

10.48550/arxiv.2502.13474 preprint EN arXiv (Cornell University) 2025-02-19

With the rapid advancement of Artificial Intelligence (AI) technologies, applications AI are transforming lifestyles across various fields at an unprecedented pace, bringing numerous conveniences and innovations. However, widespread application also presents challenges such as privacy protection ethical concerns. Therefore, it is great value to enhance insights into how being used in industries, will be developed, have healthy development technology societys well-being. In this thesis, they...

10.54254/2755-2721/2025.20074 article EN cc-by Applied and Computational Engineering 2025-01-10

Yawning detection is actively used in multimedia applications such as driver fatigue assessment and status monitoring. However, the accuracy robustness of existing yawning detectors are limited due to variations environments (especially lights), facial expressions, confusion behaviours (e.g., talking eating). This paper introduces a transformer-based method, YawnNet, for accurate by leveraging spatial-temporal encoding local cues. In particular, YawnNet contains data processing stage with...

10.1145/3652583.3657618 article EN 2024-05-30
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