A computer, including a processor and a memory, the memory including instructions to be executed by the processor to acquire a first image by illuminating a first object with a first light beam, determine a first measure of pixel values in the image and perform a comparison of the first measure of pixel values to a second measure of pixel values determined from a second image of a second object, wherein the second image is previously acquired by illuminating the second object with a second light beam. The instructions include further instructions to, when the comparison determines that the first measure is equal to the second measure of pixel values within a tolerance, determine that the first object and the second object are a same object.

A method of thermographic inspection is disclosed, including applying a thermal pulse to a surface and capturing an image of a thermal response of the surface. The image is captured with an infrared camera through a polarizer having a first orientation. The method further includes determining, by analysis of the image, whether the thermal response is indicative of a crack on the surface.

A method of thermographic inspection is disclosed, including applying a thermal pulse to a surface and capturing an image of a thermal response of the surface. The image is captured with an infrared camera through a polarizer having a first orientation. The method further includes determining, by analysis of the image, whether the thermal response is indicative of a crack on the surface.

A novel technique for automated analysis of organisms like insects, shrimp and fish. The technique comprises detection of structures and/or organs in the organisms in a flow-system. Alternatively or in addition, the technique may comprise sorting of the organisms, for example sex separation of the organisms in the flow system. The technique may comprise steps of: (a) illuminating the organisms in a detection region, (b) imaging the organisms in the detection region, with an extended depth of field that spans at least one-fourth of their thickness and from at least two different directions; (c) analyzing the images for the presence of one or more features, structures and/or organs of interest.

Provided are a device and method for designing a material using deep learning. The method includes training a decoder which derives wave properties from given information on a material in advance, training an autoencoder including the decoder and an encoder which will be trained to derive information on a material from given wave properties, and inputting targeted wave properties to the trained encoder to acquire information on a material satisfying the input wave properties.

Provided are a device and method for designing a material using deep learning. The method includes training a decoder which derives wave properties from given information on a material in advance, training an autoencoder including the decoder and an encoder which will be trained to derive information on a material from given wave properties, and inputting targeted wave properties to the trained encoder to acquire information on a material satisfying the input wave properties.

The subject disclosure relates to techniques for integrating synthetic plants into a virtual scene. A process of the disclosed technology can include receiving a digital asset comprising synthetic foliage, processing the digital asset to modify at least one parameter associated with the synthetic foliage to generate a modified digital asset, acquiring synthetic sensor data corresponding with the modified digital asset, and calculating a classification score for the modified digital asset based on the synthetic sensor data.

An image reading apparatus includes a conveyance unit configured to convey an original; a reading unit comprising a reading sensor, the reading sensor having a light receiving element to receive light of a first color and a light receiving element to receive light of a second color that is different from the first color, wherein the reading unit is configured to read an image of the original conveyed by the conveyance unit by using the reading sensor to generate image data which represents a reading result of the reading unit; at least one processor configured to: determine a first abnormal position that is a position in a first direction of an abnormal pixel of the first color in an image represented by the image data.

A biometric sensor configured to detect a biometric information is provided. The biometric sensor includes a light emitting layer and a touch detection layer; an encapsulating cover on the light emitting layer; a photo-sensing layer configured to detect at least a portion of a light totally reflected by a surface of the biometric sensor in touch with a skin of a user; a touch sensing circuit configured to determine a touch position of a touch; a processor configured to determine a scanning region based on the touch position, and configured to control the light emitting layer to form a scanning light source to scan the scanning region in a scanning pattern; and a biometric information analysis circuit configured to determine a light intensity distribution of a reflected light reflected by the surface of the biometric sensor, and configured to determine the biometric information based on the light intensity distribution.

A biometric sensor configured to detect a biometric information is provided. The biometric sensor includes a light emitting layer and a touch detection layer; an encapsulating cover on the light emitting layer; a photo-sensing layer configured to detect at least a portion of a light totally reflected by a surface of the biometric sensor in touch with a skin of a user; a touch sensing circuit configured to determine a touch position of a touch; a processor configured to determine a scanning region based on the touch position, and configured to control the light emitting layer to form a scanning light source to scan the scanning region in a scanning pattern; and a biometric information analysis circuit configured to determine a light intensity distribution of a reflected light reflected by the surface of the biometric sensor, and configured to determine the biometric information based on the light intensity distribution.