Results 221 to 230 of about 1,050,353 (272)

Long‐Tea‐CLIP: An Expert‐Level Multimodal AI Framework for Fine‐Grained Green Tea Grading Across Five Sensory Dimensions

Advanced Science, EarlyView.
Long‐Tea‐CLIP (Contrastive Language‐Image Pre‐training) presents a multimodal AI framework that integrates visual, metabolomic, and sensory knowledge to grade green tea across appearance, soup color, aroma, taste, and infused leaf. By combining expert‐guided modeling with CLIP‐supervised learning, the system delivers fine‐grained quality evaluation and
Yanqun Xu, Zhengfang Xue, Qing Luo, Xu Liu, Yongquan Xu, Jing Huang, Xingcai Zhang, Xinyuan Zhang, Zhonghua Liu, Zisheng Luo   +9 more
wiley   +1 more source

Hypothesizing mechanistic links between microbes and disease using knowledge graphs. [PDF]

Sci Rep
Santangelo BE, Bada M, Hunter LE, Lozupone C.   +3 more
europepmc   +1 more source

The analysis of artificial intelligence knowledge graphs for online music learning platform under deep learning. [PDF]

Sci Rep
Jiang S, Shi N, Liu C.
europepmc   +1 more source

Enhanced pre-recruitment framework for clinical trial questionnaires through the integration of large language models and knowledge graphs. [PDF]

Sci Rep
Zihang C, Liang L, Qianmin S, Gaoyi C, Jihan H, Ying L.   +5 more
europepmc   +1 more source

Cotton pest and disease diagnosis via YOLOv11-based deep learning and knowledge graphs: a real-time voice-enabled edge solution. [PDF]

Front Plant Sci
Zhong M, Wei L, Mo H.
europepmc   +1 more source

A novel computational analysis integrating social determinants information from EHR and literature with Alzheimer's disease biological knowledge through large language models and knowledge graphs. [PDF]

Innov Aging
Shang T, Yang S, Zhai T, He W, Mamourian E, Zhang J, Hou B, Lee J, Duong-Tran D, Moore JH, Ritchie MD, Shen L.   +11 more
europepmc   +1 more source

BioWalk-MDA: a novel approach for large-scale predicting metabolite-drug associations based on multi layered biomedical knowledge graphs. [PDF]

Brief Bioinform
Wu X, Wu M, Yang Y, Jiang S, Li G, Fu Y, Liu Z, Lv Y, Shi H.   +8 more
europepmc   +1 more source

Empowering natural product science with AI: leveraging multimodal data and knowledge graphs.

Nat Prod Rep
Meijer D, Beniddir MA, Coley CW, Mejri YM, Öztürk M, van der Hooft JJJ, Medema MH, Skiredj A.   +7 more
europepmc   +1 more source