In some implementations, a device may determine that an unknown sample is an outlier sample by using an aggregated classification model. The device may determine that one or more spectroscopic measurements are not performed accurately based on determining that the unknown sample is the outlier sample. The device may cause one or more actions based on determining the one or more spectroscopic measurements are not performed accurately.

An object recognition apparatus includes a first spectrometer configured to obtain a first type of spectrum data from light scattered, emitted, or reflected from an object; a second spectrometer configured to obtain a second type of spectrum data from the light scattered, emitted, or reflected from the object, the second type of spectrum data being different from the first type of spectrum data; an image sensor configured to obtain image data of the object; and a processor configured to identify the object using data obtained from at least two from among the first spectrometer, the second spectrometer, and the image sensor and using at least two pattern recognition algorithms.

A spectroscopic metrology system includes a spectroscopic metrology tool and a controller. The controller generates a model of a multilayer grating including two or more layers, the model including geometric parameters indicative of a geometry of a test layer of the multilayer grating and dispersion parameters indicative of a dispersion of the test layer. The controller further receives a spectroscopic signal of a fabricated multilayer grating corresponding to the modeled multilayer grating from the spectroscopic metrology tool. The controller further determines values of the one or more parameters of the modeled multilayer grating providing a simulated spectroscopic signal corresponding to the measured spectroscopic signal within a selected tolerance. The controller further predicts a bandgap of the test layer of the fabricated multilayer grating based on the determined values of the one or more parameters of the test layer of the fabricated structure.

A multispectral sensor device may include a sensor array comprising a plurality of channels and one or more processors to determine that a time-sensitive measurement is to be performed, wherein the time-sensitive measurement is to be performed using data collected by one or more channels of the plurality of channels; cause the data to be collected by a proper subset of channels, of the plurality of channels, wherein the proper subset of channels includes the one or more channels; and determine the time-sensitive measurement based on the data.

Systems and methods here may be used for automated capturing and analyzing spectrometer data of multiple sample gemstones on a stage, including mapping digital camera image data of samples, applying a Raman Probe to a first sample gemstone under evaluation on the stage, receiving spectrometer data of the sample gemstone from the probe, automatically moving the stage to a second sample, using the image data, and analyzing the other samples.

Embodiments of the present invention relate to apparatus and methods for dual comb spectroscopy with deterministic stepping and scanning of temporal pulse offset. In one embodiment, the present invention relates to a novel dual-comb spectroscopy including mode locked robust Er-combs and digital phase-locking electronics for step scanning between the two frequency combs and applicable to any phase-locked dual-comb system. The tight phase control of the DCS source allows for the control of temporal offset between the two comb pulses during measurements.

A non-contact system for the sensing of pH includes a hyperspectral imaging device configured to capture a hyperspectral image of a fluid, a flow cell configured to enable the capturing of a hyperspectral image of a fluid, a process, and a memory. The memory includes instructions stored thereon, which, when executed by the processor, cause the system to generate a hyperspectral image of the fluid in the flow cell, generate several spectral signals based on the hyperspectral image, provide the spectral signal as an input to a machine learning network, and predict by the machine learning network a pH of a fluid.

An identification apparatus 1000 includes a light collecting unit 20 configured to collect scattered light from a sample, spectroscopic elements 150l and 150h configured to disperse light from the light collecting unit 20, an imaging unit 170 that includes a plurality of light detection elements arrayed in a row direction 172r and a column direction 172c and to which optical spectra from the spectroscopic elements 150l and 150h are projected along the row direction 172r, and an acquisition unit 30 configured to acquire spectral information about the sample based on an output signal from the imaging unit 170. The optical spectra corresponding to the sample are projected to the imaging unit 170 discontinuously in at least one of the row direction 172r and the column direction 172c.

The conformal spectral library training method (CSLTM) of the disclosure allows sets of voltages for an optical filter to be calculated by way of a direct calculation without processing large amounts of spectral information, which significantly increases the speed of processing spectral information.

An optical measurement system includes a light source, a spectroscopic detector, a reference sample, a switching mechanism that switches between a first optical path through which a sample to be measured is irradiated with light from the light source and light produced at the sample is guided to the spectroscopic detector and a second optical path through which the reference sample is irradiated with light from the light source and light produced at the reference sample is guided to the spectroscopic detector, and a processing unit that calculates, by performing correction processing based on change between a first detection result at first time and a second detection result at second time, a measurement value of the sample from a third detection result provided from the spectroscopic detector as a result of irradiation of the sample with light from the light source at third time temporally proximate to the second time.