Manufacturing a device may include inspecting a surface of an inspection target device. The inspecting may include forming a metal layer on a surface of the inspection target device on which a minute pattern is formed, directing a beam of light to be incident and normal to the surface of the inspection target device, determining a spectrum of light reflected from the surface of the inspection target device, and generating, via the spectrum, information associated with a structural characteristic of the minute pattern formed on the inspection target device. The inspection target device may be selectively incorporated into the manufactured device based on the generated information.

A method for determining a quality condition of an agricultural product comprises: receiving a received light at a light detector, the received light comprising reflected, scattered, refracted, and/or deflected light from the agricultural product; transmitting the received light to a spectrometer; producing agricultural product (AP) spectral data of the received light using the spectrometer; with a computer in electrical communication with the spectrometer, comparing the AP spectral data to reference spectral data to determine whether the agricultural product has the quality condition, the reference spectral data corresponding to known quality conditions of the agricultural product; and with the computer, generating an output signal corresponding to the quality condition of the agricultural product.

Disclosed are examples of hyperspectral imager-equipped lighting devices that provide general illumination supplied by artificial or natural light, and that also detect environmental conditions in the environment around the lighting device. The hyperspectral imager detects light within a contiguous spectral band from the environment in the vicinity of the lighting device. In response, the hyperspectral imager generates image data representative of the spectral intensity of one or more subsets of a continuous spectrum of wavelengths of the detected light. A controller may analyze the image data generated by the hyperspectral imager and may initiate action to control operation of the light source or building management products based on an environmental condition detected by the analysis of the generated image data.

Disclosed are examples of hyperspectral imager-equipped lighting devices that provide general illumination supplied by artificial or natural light, and that also detect environmental conditions in the environment around the lighting device. The hyperspectral imager detects light within a contiguous data from the environment in the vicinity of the lighting device. In response, the hyperspectral imager generates image data representative of the spectral intensity distribution (e.g. intensities of a continuous range wavelengths in the optical spectrum) of the detected light. A controller may analyze the image data generated by the hyperspectral imager and may initiate action based on, or outputs a report indicating, an environmental condition detected by the analysis of the generated image data.

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.

Provided are a measurement result display device and a measurement result display method which are capable of making a list of how much difference is present between an allowable value and a measurement value of each measurement item measured by a measuring instrument, in a visually discriminable state. An allowable upper limit value indicator 21 and an allowable lower limit value indicator 22 are disposed at display positions which are set in advance in a measurement result image 20 as positions indicating an allowable upper limit value and an allowable lower limit value, and a measurement value indicator 23 is disposed at a display position calculated from display positions of the allowable upper limit value indicator 21 and allowable lower limit value indicator 22 and a measurement value measured by the measurement unit 10.

A terahertz (THz) spectral imaging system includes a THz 2D imaging camera, a tunable THz bandpass filter before the THz camera, and a broadband THz light source. The tunable THz bandpass filter includes a visible or infrared laser source, a spatial light modulator modulating the light to generate a spatially structured light pattern, and a semiconductor plate onto which the light pattern is projected. The light pattern generates carriers in the semiconductor plate to turn it into a metamaterial THz bandpass filter, which is tunable by changing the light patterns. A controller controls the light patterns and the THz camera in a timing sequence to acquire multiple 2D THz images at different THz frequencies. Such THz spectral image data can be further combined with visible images and LiDAR images in a security surveillance system to automatically detect security threats using image fusion and deep learning techniques.

A terahertz (THz) spectral imaging system includes a THz 2D imaging camera, a tunable THz bandpass filter before the THz camera, and a broadband THz light source. The tunable THz bandpass filter includes a visible or infrared laser source, a spatial light modulator modulating the light to generate a spatially structured light pattern, and a semiconductor plate onto which the light pattern is projected. The light pattern generates carriers in the semiconductor plate to turn it into a metamaterial THz bandpass filter, which is tunable by changing the light patterns. A controller controls the light patterns and the THz camera in a timing sequence to acquire multiple 2D THz images at different THz frequencies. Such THz spectral image data can be further combined with visible images and LiDAR images in a security surveillance system to automatically detect security threats using image fusion and deep learning techniques.

A method of processing hyperspectral data includes receiving the hyperspectral data. The hyperspectral data includes spectral data for each pixel in a two-dimensional array of pixels, and for each spectral band in a set of multiple spectral bands associated with each pixel. The hyperspectral data is converted into one-dimensional spectra. Each one-dimensional spectrum includes, for a single pixel of the pixels, the spectral data for each spectral band in the set of multiple spectral bands associated with the single pixel. Each one-dimensional spectrum is inputted to a trained transformer neural network. For each one-dimensional spectrum, the trained transformer neural network is used to spectrally un-mix the spectral data in the set of multiple spectral bands.

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.