A heating cooker includes a heating cavity for accommodating a heating target, an imager for capturing an image of an interior of the heating cavity, and an exposure controller for performing exposure control. The exposure controller is operable to perform the exposure control based on gray level information obtained from the image captured by the imager. As a result, it is possible to acquire an image for recognition after accurately detecting the illuminance of the interior of the heating cavity and performing exposure control.

A heating cooker includes a heating cavity for accommodating a heating target, an imager for capturing an image of an interior of the heating cavity, and an exposure controller for performing exposure control. The exposure controller is operable to perform the exposure control based on gray level information obtained from the image captured by the imager. As a result, it is possible to acquire an image for recognition after accurately detecting the illuminance of the interior of the heating cavity and performing exposure control.

A method for automatically identifying global solar photovoltaic (PV) panels based on a cloud platform by using remote sensing. Optical images in a study area for a whole specific year are collected based on the cloud platform, and preprocessing is performed to obtain a surface reflectance image. Seven time-series images are derived and constructed based on spectral features of a solar PV panel: a solar PV panel index image, a water index image, a vegetation index image, a difference image between a first shortwave infrared band and a second shortwave infrared band, a difference image between the first shortwave infrared band and a near-infrared band, a blue band image, and a first shortwave infrared band image. Data in the seven time-series images are synthesized and reconstructed to obtain input data required by a model. A remote sensing theoretical model for automatically identifying a solar PV panel is constructed.

A method for automatically identifying global solar photovoltaic (PV) panels based on a cloud platform by using remote sensing. Optical images in a study area for a whole specific year are collected based on the cloud platform, and preprocessing is performed to obtain a surface reflectance image. Seven time-series images are derived and constructed based on spectral features of a solar PV panel: a solar PV panel index image, a water index image, a vegetation index image, a difference image between a first shortwave infrared band and a second shortwave infrared band, a difference image between the first shortwave infrared band and a near-infrared band, a blue band image, and a first shortwave infrared band image. Data in the seven time-series images are synthesized and reconstructed to obtain input data required by a model. A remote sensing theoretical model for automatically identifying a solar PV panel is constructed.

A control method for an electronic device and an electronic device are provided. The electronic device includes an infrared emitter, an infrared sensor, and a visible light sensor. The control method includes: acquiring an original pixel position of a zero-level region on the infrared sensor; acquiring a human eye pixel position of a human eye region on the visible light sensor; determining whether a human eye enters the zero-level region according to the original pixel position and the human eye pixel position; and triggering a protection mechanism of the infrared emitter when the human eye enters the zero-level region.

To provide an imaging device capable of reducing discomfort caused by visible light. A light source can emit the visible light and invisible light as irradiation light. An imaging unit captures an image of an irradiation region irradiated with the irradiation light to acquire an image. A processor causes the imaging unit to acquire a detection image in a first irradiation mode in which the invisible light is emitted from the light source, and determines whether a biometric object is presented in the irradiation region based on the detection image. When the biometric object is presented, the processor causes the imaging unit to acquire the biometric image obtained by copying the biometric object as the image in a second irradiation mode in which the visible light and the invisible light are emitted from the light source.

Methods, devices, and systems related to determining biometric data using an array of infrared (IR) illuminators are described. In an example, a method can include projecting a number of IR dots on a user using a dot projector and an array of IR illuminators, capturing an IR image of the number of IR dots using an IR camera, comparing a number of pixels of the captured IR image to a number of corresponding pixels of a baseline IR image using a processing resource, and determining biometric data of the user at least partially based on comparing the captured IR image to the baseline IR image using the processing resource.

Methods, devices, and systems related to determining biometric data using an array of infrared (IR) illuminators are described. In an example, a method can include projecting a number of IR dots on a user using a dot projector and an array of IR illuminators, capturing an IR image of the number of IR dots using an IR camera, comparing a number of pixels of the captured IR image to a number of corresponding pixels of a baseline IR image using a processing resource, and determining biometric data of the user at least partially based on comparing the captured IR image to the baseline IR image using the processing resource.

A hybrid inference facility receives a sequence of data items. For each data item, the facility: forwards the data item to a server; subjects it to a local machine learning model to produce a local inference result for the data item; and the local inference result to a queue; aggregates the inference results contained by the queue to obtain an output inference result; and removes the oldest inference result from the queue. The facility receives from the server cloud inference results each obtained by applying a server machine learning model to one of the data items forwarded to the server. For each received cloud inference result, the facility substitutes the cloud inference result in the queue for the local inference result for the same data item.

An aspect of the invention provides a method for determining at least one internal quality attribute of an article (102) of in agricultural produce. The method includes receiving a plurality of first spectroscopic values obtained from directing low band light in a first wavelength associated to a low band of wavelengths from at least one low band light source (104) at least partly through the article (102) toward at least one detector (120); receiving a plurality of second spectroscopic values obtained from directing high band light in a second wavelength associated to a high band of wavelengths from at least one high band light source (106) at least partly through the article (102) toward the at least one detector (120); determining at least one measured spatial profile associated to the article, the at least one measured spatial profile comprising at least one of a plurality of ratios of respective first spectroscopic values to respective second spectroscopic values, a plurality of ratios of respective second spectroscopic values to respective first spectroscopic values; and determining the at least one internal quality attribute at least partly from a comparison of the at least one measured spatial profile with at least one reference spatial profile associated to a class of articles of agricultural produce.