Described herein is an object recognition system in low illumination conditions. A 3D InIm system can be trained in the low illumination levels to classify 3D objects obtained under low illumination conditions. Regions of interest obtained from 3D reconstructed images are obtained by de-noising the 3D reconstructed image using total-variation regularization using an augmented Lagrange approach followed by face detection. The regions of interest are then inputted into a trained CNN. The CNN can be trained using 3D InIm reconstructed under low illumination after TV-denoising. The elemental images were obtained under various low illumination conditions having different SNRs. The CNN can effectively recognize the 3D reconstructed faces after TV-denoising.

Provided is an imaging device that includes a plurality of pixels, a memory unit, a memory control unit, and a bus interface. Each of the memory unit, the plurality of pixels, the memory control unit, and the bus interface is in any one of a plurality of semiconductor substrates. The plurality of pixels performs photoelectric conversion. The memory unit stores image data generated on the basis of a result of the photoelectric conversion. The memory control unit performs a read operation on the basis of first internal address information. The read operation is for reading, from the memory unit, image data corresponding to the first internal address information among pieces of the image data. The bus interface performs communication for first address information with an external device, supplies the memory control unit with the first internal address information, and transmits the read image data to the external device.

An optical module includes: a first lens having a first principal surface and a second principal surface; and a second lens having a third principal surface and a fourth principal surface, the first principal surface is configured by a flat surface, and on the second principal surface, a concave lens array having a plurality of concave lenses is formed, and on each of the third principal surface and the fourth principal surface, a convex lens array having a plurality of convex lenses is formed, and the second principal surface and the third principal surface are arranged in such a way as to face each other.

An optical module includes: a first lens having a first principal surface and a second principal surface; and a second lens having a third principal surface and a fourth principal surface, the first principal surface is configured by a flat surface, and on the second principal surface, a concave lens array having a plurality of concave lenses is formed, and on each of the third principal surface and the fourth principal surface, a convex lens array having a plurality of convex lenses is formed, and the second principal surface and the third principal surface are arranged in such a way as to face each other.

An electronic device is disclosed, which includes: a first substrate having a display area comprising a biometric sensing region and a non-sensing region; a biometric sensing module disposed corresponding to the biometric sensing region; a light altering member at least partially formed in the biometric sensing region, wherein the light altering member comprises a reflecting layer and the reflecting layer comprises a plurality of openings; and a supporting film disposed under the first substrate and contacting the first substrate, wherein a reflectivity of the biometric sensing region is greater than a reflectivity of the non-sensing region, the supporting film comprises a hole, and the biometric sensing module disposed corresponding to the hole.

An electronic device is disclosed, which includes: a first substrate having a display area comprising a biometric sensing region and a non-sensing region; a biometric sensing module disposed corresponding to the biometric sensing region; a light altering member at least partially formed in the biometric sensing region, wherein the light altering member comprises a reflecting layer and the reflecting layer comprises a plurality of openings; and a supporting film disposed under the first substrate and contacting the first substrate, wherein a reflectivity of the biometric sensing region is greater than a reflectivity of the non-sensing region, the supporting film comprises a hole, and the biometric sensing module disposed corresponding to the hole.

An ultrasonic signal detecting circuit, an ultrasonic signal detecting method, and a display panel. The ultrasonic signal detecting circuit includes a control sub-circuit and a sensing sub-circuit. The sensing sub-circuit detects an ultrasonic echo signal, and generates a piezoelectric signal, which includes a first sub signal and a second sub-signal, according to the ultrasonic echo signal, the voltage value of one of the first and second sub-signals are higher than the value of a reference voltage signal, and that of the other one of the first and second sub-signals are lower than the reference voltage signal. The control sub-circuit is electrically connected to the sensing sub-circuit. Under control of the first sub-signal, a first power supply end and an output end of the control sub-circuit are turned on; and under control of the second sub-signal, the first power supply end and the output end of the control sub-circuit are turned on.

A thin lightweight imaging device is provided. A highly convenient imaging device is provided. The imaging unit includes an imaging unit, a memory, and an arithmetic circuit. The imaging unit includes a light-receiving device, a first light-emitting device, and a second light-emitting device. The first light-emitting device has a function of emitting light in a wavelength range that is different from a wavelength range of light emitted by the second light-emitting device. The imaging unit has a function of making the first light-emitting device emit light and acquiring first image data. The imaging unit has a function of making the second light-emitting device emit light and acquiring second image data. The memory has a function of retaining the first reference data and the second reference data. The arithmetic circuit has a function of correcting the first image data with the use of the first reference data retained in the memory and calculating first correction image data. The arithmetic circuit has a function of correcting the second image data with the use of the second reference data retained in the memory and calculating second correction image data. The arithmetic circuit has a function of combining the first correction image data and the second correction image data to generate synthesized image data. The light-receiving device includes a first pixel electrode, and the first light-emitting device includes a second pixel electrode on the same plane as the first pixel electrode.

A method for assisting operation of a vehicle traveling on a roadway includes acquiring visual images around the vehicle with at least one visual camera having a field of view and acquiring thermal images around the vehicle with at least one thermal camera having the field of view. The thermal images are superimposed over the visual images to produce composite images. An object is detected in the composite images. A vehicle assist system adjusts at least one of a direction of travel and speed of the vehicle in response to detecting the object.

A computational cytometer operates using magnetically modulated lensless speckle imaging, which introduces oscillatory motion to magnetic bead-conjugated rare cells of interest through a periodic magnetic force and uses lensless time-resolved holographic speckle imaging to rapidly detect the target cells in three-dimensions (3D). Detection specificity is further enhanced through a deep learning-based classifier that is based on a densely connected pseudo-3D convolutional neural network (P3D CNN), which automatically detects rare cells of interest based on their spatio-temporal features under a controlled magnetic force. This compact, cost-effective and high-throughput computational cytometer can be used for rare cell detection and quantification in bodily fluids for a variety of biomedical applications.