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公开(公告)号：US20240145040A1
公开(公告)日：2024-05-02
申请号：US18496650
申请日：2023-10-27
申请人： Hyperspectral Corp.
发明人： Euan F. Mowat , Matthew Theurer , Zachary Shaffer
摘要： An example method comprising: receiving a first set of intensity values based on a first set of intensity measurements for a set of wavelengths, the set of intensity measurements obtained by an apparatus configured to generate light and another light, detect the light that has passed through a portion of a sample, and measure intensity of the light by optical sensor, an angle separating the optical sensor and apparatus; applying a trained model to obtain a result; based on the result, determining a subset of wavelengths; receiving another set of intensity values, another set of intensity values being based on another set of intensity measurements for the set of wavelengths, the other set of intensity measurements obtained by the other light, detect the other light that has passed through another portion of the sample, and measure intensity by the optical sensor, another angle separating the optical sensor and the apparatus, the angles being different, applying another trained model to obtain another result, trained models being different from each other; applying the results to a trained multi-model to determine a positive or a negative pathogen detection for the pathogen in the sample, generating a notification and providing the notification.
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公开(公告)号：US20240027266A1
公开(公告)日：2024-01-25
申请号：US18358798
申请日：2023-07-25
申请人： Hyperspectral Corp.
CPC分类号： G01J3/0275 , G01J3/0267 , G01J3/0264 , G01J3/42 , G01J3/501 , G01J2003/2836
摘要： An example method includes receiving a first set of data that includes spectral metrics provided by a spectral acquisition apparatus that obtains the spectral metrics based on interactions of electromagnetic radiation with a sample. The first set of data is processed to obtain a second set of data that includes the spectral metrics. One or more trained models are applied to the spectral metrics or a set of values based on the spectral metrics to obtain a result. Based on the result, either a positive particle of interest detection or a negative particle of interest detection for the particle of interest for the sample is determined. A particle of interest detection notification that indicates either the positive particle of interest detection or the negative particle of interest detection for the particle of interest for the sample may be generated and provided.
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