Abstract: An augmented reality (AR) display is provided. The display comprises a light field generator and a birdbath eyepiece. The light field generator generates a light field as an output. The birdbath eyepiece connects to the light field generator for receiving and projecting the light field to human eye. The birdbath eyepiece comprises a beam splitter and a combiner. The combiner has a curved surface. Each beam of the light field is split into two beams by the beam splitter with one of the split beams reflected by the combiner. Three states-of-use of the birdbath eyepiece are provided for the near-eye light field AR display to transmit the light field to the human eye. A low f-number (or focal ratio) and a large eyebox are obtained to effectively expand the field of view and increase the volume of space within which the human eye can receive the light field.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, an identity of a vehicle operator may be determined and a vehicle operator profile and/or operating data regarding autonomous operation features of the vehicle may be received after the vehicle operator opts into a rewards program and agrees to share their data. Autonomous operation and vehicle operator risk levels associated with operation of the autonomous or semi-autonomous vehicle may be determined. Based upon the risk levels and/or comparison thereof, one or more autonomous operation features may be disengaged. A preparedness level of the vehicle operator to assume or reassume control of operating the vehicle is determined prior to disengagement. If satisfactory, an alert is presented to the vehicle operator prior to disengagement of the autonomous operation features.

Abstract: An image recognition method applied to an electronic device is provided. The method includes obtaining a recognition region and a plurality of test regions. A plurality of first prediction results is obtained by predicting each of the plurality of test regions using a first recognition model. A prediction accuracy rate is calculated. A plurality of target regions is obtained from the plurality of test regions, and a second recognition model is obtained by adjusting the first recognition model based on the prediction accuracy rate and the plurality of target regions. An initial feature matrix is obtained by inputting the recognition region in the second recognition model. A target vector is generated according to a target feature matrix and an initial weight matrix; and a recognition result of the image to be recognized is obtained by inputting the target vector into the second recognition model.

Abstract: An image classification method applied to an electronic device is provided. The method includes obtaining prediction results of a plurality of test images. A plurality of target images is determined according to the prediction results, and a prediction accuracy rate of a first classification model is calculated based on the plurality of target images. A second classification model is obtained according to the plurality of target images. An initial feature matrix is obtained using the second classification model. An input feature matrix is obtained by performing a dimension raising process on an initial feature matrix. Once a target weight matrix is obtained based on an initial weight matrix, and a target vector is generated according to the target weight matrix and the input feature matrix, a classification result of an image to be classified is obtained by inputting the target vector into a classification layer.

Abstract: A method for identifying images of any kind of object, applied in an electronic device, obtains images to be classified, and obtains classification models and target models. Image segmentation on the images is carried out and target images are obtained; target images are input into each of the input layers and target feature maps are generated; target values according to size of each target feature map are generated; a convolution operation on the target feature maps generates feature values and a target vector of each target model is generated according to average pooling layers, feature values, and target values. The target vector is input into classification layers of a target model and label categories and probability values of categories obtained, enabling classification of images according to the label categories and the probability values of categories.

Abstract: A movement detection method, applied to a navigation input device with a navigation pattern comprising a center pattern and a radial pattern. The movement detection method comprises: (a)capturing a sensing image comprising a center pattern image and at least portion of a radial pattern image by an image sensor, wherein the center pattern image corresponds to the center pattern and the radial pattern image corresponding to the radial pattern; (b)computing a translation of the navigation input device according to shift of the center pattern image; and (c)computing a rotation angle of the navigation input device according to a first pattern relation between the center pattern image and a first portion of the radial pattern image. The translation and the rotation angle can be precisely and sensitively detected even if the joystick device is miniaturized, since the translation and the rotation angle are computed according to the navigation pattern.

Abstract: An anti-peep display device includes a display module and an anti-peep module disposed on the display module. The anti-peep module includes the following features. The first light incident surface faces the display surface, the second and third light incident surfaces are located on opposite sides of the first light incident surface, the first condensing portion is disposed corresponding to the second light incident surface and the first light source, the second condensing portion is disposed corresponding to the third light incident surface and the second light source, the first and second condensing portions convert beams of the first and second light sources into anti-peep beams with a beam angle less than 10 degrees, and the optical microstructures reflect the anti-peep beams and exit the anti-peep beams from the light guide plate. The present invention also provides an anti-peep method applicable to the anti-peep display device.

Abstract: A steel panel damper is provided for reinforcing a building structure. The steel panel damper is disposed between a first member and an opposite second member arranged in the building structure. The steel panel damper comprises a first elastic segment, a second elastic segment, an energy dissipation segment, a first end plate, and a second end plate. In terms of the cross-sectional area perpendicular to the first direction, the first elastic segment and the second elastic segment are greater than the energy dissipation segment.

Abstract: A fan control method, a processing device, and a fan control system are provided. The fan control method includes: obtaining at least one temperature-fan speed table and at least one current-fan speed table corresponding to each of at least one fan device; obtaining an estimated temperature value corresponding to a predetermined area according to a sensing result of at least one temperature sensor disposed in the predetermined area; obtaining rotational speed information of a target rotational speed of the at least one fan device according to the estimated temperature value and the at least one temperature-fan speed table; and providing the rotational speed information to a controller configured to control a fan speed in the at least one fan device.

Abstract: An X-ray device, including a sensor panel and a flexible scintillator structure disposed on the sensor panel, is provided. A manufacturing method of the X-ray device is also provided.

Abstract: According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver—the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated.

Abstract: The present disclosure provides a semiconductor structure and a method of manufacturing the same. The semiconductor structure includes a sensing device, a solar cell, and an interconnecting structure. The solar cell is disposed above the sensing device and is electrically connected to the sensing device. The interconnecting structure is disposed between the sensing device and the solar cell and has a first surface facing the solar cell and a second surface facing the sensing devices. The interconnecting structure comprises a first energy storage component and a second energy storage component. The first energy storage component is disposed closer to the first surface of the interconnecting structure than the second energy storage component.

Abstract: An integrated chip including a gate layer. An insulator layer is over the gate layer. A channel structure is over the insulator layer. A pair of source/drains are over the channel structure and laterally spaced apart by a dielectric layer. The channel structure includes a first channel layer between the insulator layer and the pair of source/drains, a second channel layer between the insulator layer and the dielectric layer, and a third channel layer between the second channel layer and the dielectric layer. The first channel layer, the second channel layer, and the third channel layer include different semiconductors.

Abstract: A high-voltage semiconductor device structure is provided. The high-voltage semiconductor device structure includes a semiconductor substrate, a source ring in the semiconductor substrate, and a drain region in the semiconductor substrate. The high-voltage semiconductor device structure also includes a doped ring surrounding sides and a bottom of the source ring and a well region surrounding sides and bottoms of the drain region and the doped ring. The well region has a conductivity type opposite to that of the doped ring. The high-voltage semiconductor device structure further includes a conductor electrically connected to the drain region and extending over and across a periphery of the well region. In addition, the high-voltage semiconductor device structure includes a shielding element ring between the conductor and the semiconductor substrate. The shielding element ring extends over and across the periphery of the well region.

Abstract: A method for detecting image sizes using a computer device is provided. In the method, the computer device obtains a pre-trained image processing model and an input image, establishes a stack according to a number of network layers of the pre-trained image processing model. Output feature maps are obtained by processing the input image using the pre-trained image processing model. Image sizes of the output feature maps are detected. The image sizes are written into the stack in sequence, and the network layers deleted iteratively in an order from large to small according to an execution sequence of the network layers of the pre-trained image processing model until the stack is full. By performing the method, output sizes of the input image can be obtained, and a detection efficiency of image sizes can be improved.

Abstract: The image sensing structure includes a first semiconductor device and a second semiconductor device. The first semiconductor device includes at least one first unit. The at least one first unit includes a plurality of first interconnects adjacent to the top side of the first semiconductor device, a row selector, and an analog-to-digital converter (ADC) connected to the row selectors. The second semiconductor device includes at least one second unit. The at least one second unit includes a photodiode facing the top side of the second semiconductor device. The photodiode is configured to receive the light incident on the top side of the second semiconductor device. The top side of the first semiconductor device is bonded to the bottom side of the second semiconductor device.

Abstract: A semiconductor device structure includes a fin structure formed over a substrate. The structure also includes nanostructures formed over the fin structure. The structure also includes a gate structure wrapped around the nanostructures. The structure also includes a first inner spacer formed beside the gate structure. The structure also includes a second inner spacer formed beside the first inner spacer. The structure also includes spacer layers formed over opposite sides of the gate structure above the nanostructures. The structure also includes source/drain epitaxial structures formed over opposite sides of the fin structure. The second inner spacer is partially embedded in the source/drain epitaxial structures.

Abstract: A method for predicting clinical severity of a neurological disorder includes steps of: a) identifying, according to a magnetic resonance imaging (MRI) image of a brain, brain image regions each of which contains a respective portion of diffusion index values of a diffusion index, which results from image processing performed on the MRI image; b) for one of the brain image regions, calculating a characteristic parameter based on the respective portion of the diffusion index values; and c) calculating a severity score that represents the clinical severity of the neurological disorder of the brain based on the characteristic parameter of the one of the brain image regions via a prediction model associated with the neurological disorder.

Abstract: Various embodiments of the present disclosure are directed towards a camera module comprising flat lenses. Flat lenses have reduced thicknesses compared to other types of lenses, whereby the camera module may have a small size and camera bumps may be omitted or reduced in size on cell phones and the like incorporating the camera module. The flat lenses are configured to focus visible light into a beam of white light, split the beam into sub-beams of red, green, and blue light, and guide the sub-beams respectively to separate image sensors for red, green, and blue light. The image sensors generate images for corresponding colors and the images are combined into a full-color image. Optically splitting the beam into the sub-beams and using separate image sensors for the sub-beams allows color filters to be omitted and smaller pixel sensors. This, in turn, allows higher quality imaging.

Abstract: A locking device for a window or a door, wherein the window or the door has a sash slidable in a horizontal direction within a frame. When a user turns on a switch to control a block to move from the first position to the second position, the block protrudes out of a vertical surface of the sash, thereby driving a linkage member to disengage from the frame. At this time, the user could hold and push the block in the horizontal direction to move the sash between a third position and a fourth position. When the sash is pushed back to the third position, the block could be controlled to move back to the first position, namely back to a mounting groove, thereby moving the linkage member to a position where the linkage member is engaged with the frame. A method of operating thereof is provided as well.