HR-Net: A Landmark Based High Realistic Face Reenactment Network

Ren, Qiuyu; Lu, Zhiying; Wu, Haopeng; Zhang, Jianfeng; Dong, Zijian

doi:10.1109/tcsvt.2023.3268062

Cited by 8 publications

(1 citation statement)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They accurately assessed the lameness status of broilers by successively extracting keypoints into the LSTM model and classifying the lameness degree of broilers according to the six-point assessment method. To further improve detection accuracy Lin et al [14] first estimated bird keypoints using HRNet to generate global and local features [15]. After that, the excitation region was localized by keypoint clustering.…”

Section: Commercial Toolsmentioning

confidence: 99%

AI-Enabled Animal Behavior Analysis with High Usability: A Case Study on Open-Field Experiments

Chen,

Jiao,

Song

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

In recent years, with the rapid development of medicine, pathology, toxicology, and neuroscience technology, animal behavior research has become essential in modern life science research. However, the current mainstream commercial animal behavior recognition tools only provide a single behavior recognition method, limiting the expansion of algorithms and how researchers interact with experimental data. To address this issue, we propose an AI-enabled, highly usable platform for analyzing experimental animal behavior, which aims to provide better flexibility, scalability, and interactivity to make the platform more usable. Researchers can flexibly select or extend different behavior recognition algorithms for automated recognition of animal behaviors or experience more convenient human-computer interaction through natural language descriptions only. A case study at a medical laboratory where the platform was used to evaluate behavioral differences between sick and healthy animals demonstrated the high usability of the platform.

show abstract

Section: Commercial Toolsmentioning

confidence: 99%