Results 121 to 130 of about 11,320,128 (203)

Hyperspectral Imaging-Based Rapid Assessment of Chinese Yam Quality for Dried Slice Processing. [PDF]

Foods
Shen T, Yang Y, Yang D, Chen C, Zhai X, Li Z, Zhang J, Zhang R, Wang T, Huang X, Shi J.   +10 more
europepmc   +1 more source

Low-Intervention Boundary-Risk Graph Calibration for Cross-Domain Few-Shot Hyperspectral Image Classification. [PDF]

Sensors (Basel)
Zhang Y, Fan Y, Wang W.
europepmc   +1 more source

Evaluation of the Usefulness of Machine Learning and Artificial Intelligence on Hyperspectral Images in the Diagnosis of Myelodysplastic Syndrome. [PDF]

J Biophotonics
Ueda Y, Ogawa T, Wada A, Tate G, Baba Y, Baba Y, Fukuda T, Yamochi T.   +7 more
europepmc   +1 more source

HS-RankFormer for efficient and robust RGB-to-Hyperspectral image reconstruction across domains. [PDF]

Sci Rep
Vamsi B, Mahanty M, Jagan BOL, Rai HM, Agarwal S, Pak W.   +5 more
europepmc   +1 more source

Feasibility of Hyperspectral Imaging and Machine Learning for Rapid Prescreening of Aflatoxin B₁ in Maize Kernels. [PDF]

Toxins (Basel)
Jiang Y, Tai B, Yang Y, Zhang X, Jin J, Xing F.   +5 more
europepmc   +1 more source

Emerging non-invasive tools for hair follicle assessment: a narrative review on hyperspectral and terahertz imaging. [PDF]

Lasers Med Sci
Bose D, Kapoor R, Das D, Shome D, Ahmed E.   +4 more
europepmc   +1 more source

MHENet: a multimodal hybrid enhancement network for accurate classification of unsound maize kernels. [PDF]

Front Plant Sci
Wan C, Li R, Li W, Li P.
europepmc   +1 more source

Assessment of cold atmospheric pressure plasma therapy initiated at peak severity in a mouse model of radiation dermatitis. [PDF]

Sci Rep
Bernhardt T, Schlie C, Bauer J, Sperlich K, Stachs O, Bekeschus S, Friedrich O, Vollmar B, Emmert S, Boeckmann L.   +9 more
europepmc   +1 more source

Enhanced RX-Based Hyperspectral Anomaly Detection Using Laplacian-Regularized PCA. [PDF]

J Imaging
Küçük F.
europepmc   +1 more source

A hyperspectral imaging framework integrating band selection and deep learning for beverage stain classification in forensic analysis. [PDF]

Sci Rep
Shit J, Roy PP, Manikandan VM.
europepmc   +1 more source