no code implementations • 13 Oct 2023 • Yufei Liu, Manzhou Li, Qin Ma
This study proposes a method based on lightweight convolutional neural networks (CNN) and generative adversarial networks (GAN) for apple ripeness and damage level detection tasks.
3 code implementations • 10 May 2023 • Sebastian Lobentanzer, Shaohong Feng, The BioChatter Consortium, Andreas Maier, Cankun Wang, Jan Baumbach, Nils Krehl, Qin Ma, Julio Saez-Rodriguez
Current-generation Large Language Models (LLMs) have stirred enormous interest in recent months, yielding great potential for accessibility and automation, while simultaneously posing significant challenges and risk of misuse.
2 code implementations • 20 Apr 2023 • Jiaxin Wang, Heidi J. Renninger, Qin Ma, Shichao Jin
Automated stomata detection and measuring are vital for understanding plant physiological performance and ecological functioning in global water and carbon cycles.
no code implementations • 5 May 2019 • Gaoyang Li, Jinyu Yang, Chunguo Wu, Qin Ma
Recent researchers reveal that maximizing the margin distribution of whole training dataset rather than the minimal margin of a few support vectors, is prone to achieve better generalization performance.