[HTML][HTML] Improved YOLOv8 Model for Phenotype Detection of Horticultural Seedling Growth Based on Digital Cousin

Y Song, L Yang, S Li, X Yang, C Ma, Y Huang… - Agriculture, 2024 - mdpi.com
Crop phenotype detection is a precise way to understand and predict the growth of
horticultural seedlings in the smart agriculture era to increase the cost-effectiveness and …

TrojanRobot: Physical-World Backdoor Attacks Against VLM-based Robotic Manipulation

X Wang, H Pan, H Zhang, M Li, S Hu, Z Zhou… - arxiv preprint arxiv …, 2024 - arxiv.org
Robotic manipulation in the physical world is increasingly empowered by\textit {large
language models}(LLMs) and\textit {vision-language models}(VLMs), leveraging their …

Dynamics as Prompts: In-Context Learning for Sim-to-Real System Identifications

X Zhang, S Liu, P Huang, WJ Han, Y Lyu, M Xu… - arxiv preprint arxiv …, 2024 - arxiv.org
Sim-to-real transfer remains a significant challenge in robotics due to the discrepancies
between simulated and real-world dynamics. Traditional methods like Domain …

Trustworthy Transfer Learning: A Survey

J Wu, J He - arxiv preprint arxiv:2412.14116, 2024 - arxiv.org
Transfer learning aims to transfer knowledge or information from a source domain to a
relevant target domain. In this paper, we understand transfer learning from the perspectives …

CDGFD: Cross-Domain Generalization in Ethnic Fashion Design Using LLMs and GANs: A Symbolic and Geometric Approach

M Deng, L Chen - IEEE Access, 2024 - ieeexplore.ieee.org
In this paper, we propose a novel framework that leverages Large Language Models (LLMs)
and Generative Adversarial Networks (GANs) to address the challenges of cross-domain …