Results 201 to 210 of about 98,568 (293)

Enhancing Fritillariae Cirrhosae Bulbus authentication via Mask-AIR: a masked autoencoder driven information reconstruction and iterative attention framework for multi-view fusion. [PDF]

Front Nutr
Du H, Gu X, Zhu H, Chen Y, Wang X, Zhi X, Lei Z, Qu X, Fan G.   +8 more
europepmc   +1 more source

Guiding the AI revolution in periodontology and implant dentistry: Concepts, ethics, accountability, and a roadmap for sustainable adoption

Periodontology 2000, EarlyView.
Abstract Background Artificial intelligence (AI) is increasingly gaining attention in the field of periodontology and implant dentistry. Currently developed models can support diagnosis, treatment planning, and maintenance monitoring. However, most of the available literature is based on retrospective and often single‐modality data sets.
Aminollah Khormali, Negin Soghli, Patricia A. Miguez   +2 more
wiley   +1 more source

Integrating hyperspectral features and physiological parameters for quantitative estimation of fig rust severity. [PDF]

Front Plant Sci
Li Y, Chen X, Din Y, Liu H, Wang Y, Cao B, Fang X, Wang Y, Zhang Z.   +8 more
europepmc   +1 more source

Enhanced Esophageal Cancer Detection Using Spectrum‐Aided Vision Enhancer: A Comparative Study of White Light Imaging, Narrow‐Band Imaging, and Algorithmic Narrow‐Band Imaging‐Like Imaging

DEN Open, Volume 7, Issue 1, April 2027.
ABSTRACT Background and Aims Esophageal squamous cell carcinoma (ESCC) detection is crucial for improving survival. While narrow‐band imaging (NBI) improves mucosal visualization, limitations remain. We evaluated the diagnostic performance of the Spectrum‐Aided Vision Enhancer (SAVE), an algorithmic NBI‐like technology reconstructed from white light ...
Jer‐Wei Wu, Yao‐Kuang Wang, Arvind Mukundan, Riya Karmakar, Nguyen Ngoc Quynh Nhu, Yaswanth Nagisetti, Wei‐Chih Liao, Ming‐Lun Han, I‐Chen Wu, Hsiang‐Chen Wang   +9 more
wiley   +1 more source

Multi‐Model Fruit Quality Assessment With Coarse YOLOv11 Presence Filtering, Vision Transformers and the Segment Anything Model

Applied AI Letters, Volume 8, Issue 1, February 2027.
This paper presents a multi‐model deep learning pipeline for coarse fruit‐presence filtering, ripeness classification and pixel‐level spoilage segmentation. YOLOv11n is used only as an image‐level presence filter, four classifiers predict one of nine ripeness classes across three fruit types and the Segment Anything Model (SAM ViT‐H) generates fine ...
Md. Fazlay Rabbi, Al Hasib Mahamud, Md. Redwan Hossen, Md. Jakaria Mahmud, Mustofa Ahmed   +4 more
wiley   +1 more source

Deep-Learning-Driven High-Fidelity In Vivo Hyperspectral Fluorescence Imaging Under Extreme Photon-Limited Conditions. [PDF]

Adv Sci (Weinh)
Li R, Wu S, Li K, An Z, Ben Y, Li G, Kumar S, Mcginty J, Hasan T, Fu S, Zhang M, Chen L.   +11 more
europepmc   +1 more source

Assessment of corn chlorophyll content via UAV‐derived vegetative indices across growth stages

Agrosystems, Geosciences &Environment, Volume 9, Issue 4, December 2026.
Abstract Traditional chlorophyll (Chl) assessment methods are labor‐intensive and spatially limited. This study evaluated unmanned aerial vehicle (UAV) multispectral imagery for nondestructive field‐scale canopy Chl estimation in corn (Zea mays L.) to support precision nutrient management.
Aarati Khulal, Huijie Gan, Jitender Rathore, Sheetal Kumari, Ivy Flory, Caleb Bishop, Santosh Rijal, Olga Walsh   +7 more
wiley   +1 more source

Hyperspectral Imaging for Agricultural and Food Sensing: Applications, Data Analytics, and Deployment Challenges. [PDF]

Foods
Wen D, Dong Y, Hu L, Cao D, Li J.
europepmc   +1 more source

Non‐Destructive Analysis of Phenolic and Flavonoid Contents in Medicinal Plant Powders Using Hyperspectral Imaging and Variable Selection

Analytical Science Advances, Volume 7, Issue 2, December 2026.
ABSTRACT Phenolic and flavonoid contents in medicinal plants are essential to their growth and development and provide numerous health benefits, yet their quantification using traditional wet chemistry is labor‐intensive and time‐consuming. This study utilized the combination of two benchtop hyperspectral imaging (HSI) systems, namely short‐wave ...
Rahul Joshi, Sushma Kholiya, Himanshu Pandey, Mahipal Singh, Ameeta Tiwari, Jinsu Lim, Ramaraj Sathasivam, Mohammad Akbar Faqeerzada, Sang Un Park, Byoung‐Kwan Cho   +9 more
wiley   +1 more source

Hyperspectral dual-comb compressive ghost imaging with deep learning reconstruction. [PDF]

Light Sci Appl
Suh MG, Dang D, Gao M, Jin Y, Shin DC, Gupta A, Park BJ, Uzundal C, Hu B, Kort-Kamp WJM, Lee HWH.   +10 more
europepmc   +1 more source