Abstract: An image authentication method is provided. An original image is divided into blocks. An interpolation algorithm is performed on each block so as to obtain a first image. Each pixel in the first image is mapped into an index based on a palette compression technique, so as to generate a second image. Each index is divided into multiple secret values, and a secret sharing algorithm is performed based on the secret values to obtain multiple partial shares. A transparent map is generated according to the partial shares, and a lossless image filed is generated by combining the original image with the transparent map.

Abstract: A method (200) and apparatus (1100) for generating quantitative data for biliary tree structures from volumetric medical imaging scan data. The method comprises performing segmentation (230; 300) of a volume of the medical imaging scan data to identify tubular biliary structures within the volume of the medical imaging scan data; for at least one segmented tubular biliary structure within the volume of the medical imaging scan data, computing (240; 800) at least one set of quantitative structural parameters for at least one location along the length of the tubular biliary structure; and outputting (250) quantitative biliary tree data comprising the at least one set of quantitative structural parameters for the at least one segmented tubular biliary structure.

Abstract: An image data processing method includes receiving, from an image sensor, frame image data of a frame at a first resolution, reducing a resolution of the frame image data to a second resolution, performing image recognition on the frame image data to determine one or more regions of interest (ROI) and a priority level of each of the one or more ROIs, and extracting portions of the frame image data corresponding to the one or more ROIs. The method further includes modifying a resolution of the portions of the frame image data corresponding to the one or more ROIs based on the priority level of the ROIs, and combining the resolution-modified portions of the frame image data corresponding to the one or more ROIs with the frame image data at the second resolution to generate output frame image data.

Abstract: A method of processing video data includes processing a first frame to generate first feature data, which is processed to generate first classification data. The first classification data is used to determine that a first class of object is present in the first frame. The first feature data is processed to determine a portion of the first frame in which an object of the first class is located. A portion of a second frame is determined in dependence on the determined portion of the first frame. A second set of classifiers is selected on the basis of the first classification data. The second frame is processed to generate second feature data. A portion of the second feature data is processed, using the second set of classifiers, to generate second classification data for determining whether the first class of object is present in the determined portion of the second frame.

Abstract: A radio communication system of an example includes: a first radio base station which includes an antenna including antenna elements, and configured to transmit signals from the antenna elements; and user equipment. The user equipment selects a desired signal for the user equipment by taking into account reception characteristics of the respective signals transmitted by the radio base station, and transmits a signal selection indicator to the radio base station. Based on the signal selection indicator, the radio base station determines an antenna element to transmit a signal for communications with the user equipment, and transmits a data signal precoded using a predetermined precoding vector to the user equipment.

Abstract: A vehicle exterior environment recognition apparatus includes first and luminance-image acquiring units, first and second distance-image generating units, and a composite-image generating unit. The first luminance-image acquiring unit acquires first luminance images captured by image-capturing units that are disposed at positions different from each other at a first exposure time. The second luminance-image acquiring unit acquires second luminance images captured by the image-capturing units at a second exposure time shorter than the first exposure time. The first distance-image generating unit generates a first distance image through pattern matching of the first luminance images. The second distance-image generating unit generates a second distance image through pattern matching of the second luminance images.

Abstract: The present disclosure relates to the field of early non-invasive diagnosis, and specifically, to a method of determining a virtual hepatic venous pressure gradient. The method includes: constructing a 3-dimensional (3D) hepatic vein-portal vein model; establishing a finite element division mathematical model; and applying fluid dynamics to compute and simulate a virtual hepatic venous pressure gradient (vHVPG). The method optimizes and improves a more complete 3D hepatic vein-portal vein model, finite element division, and fluid dynamic simulation computation, constructing and validating a new vHVPG determination technology providing better diagnosis, providing a safe, non-invasive, accurate, and quantitative method for early non-invasive diagnosis of a portal vein high pressure patient.

Abstract: Techniques to improve the quality of captured images by reducing the effects of undesired objects (e.g., screen glare) are disclosed. The techniques may involve the use of face detection to localize the likely position of screen glare within the captured images (e.g., on a user's eyeglasses), as well as an awareness of the content that is being displayed on a display screen (or other light-projecting element projecting light into the scene) at the moment of capture of the respective image. The techniques may then model the position, size, and/or distortion of the screen contents (or other projected light) reflected by the user's eyeglasses (or other reflective surface in the captured scene environment). Once the appearance of the undesired screen glare has been modeled in the captured image, the techniques may perform an image modification operation to remove or reduce the undesired glare from the originally-acquired image in an efficient manner.

Abstract: A method is for creating a classification unit for the automatic classification of materials. An embodiment of the method includes provision of a learning computing device; provision of a start classification unit; provision of a reference image set including spectral reference recordings with annotated materials; and training of the classification unit with the reference recording set. Furthermore, a classification method is for the automatic classification of materials in an image recording. An embodiment of the classification method includes provision of a trained classification unit; provision of a spectral image recording; examination of the image recording for materials via the classification unit; and identification of the determined materials. Furthermore, a classification unit, a learning computing device, a control device and a medical imaging system are disclosed.

Abstract: A method for random access for beam failure recovery. In the method, specific random access configuration for the beam failure recovery is received. In the event of a beam failure, a random access procedure is performed according to the specific random access configuration.

Abstract: A high-precision intelligent detection method for bridge diseases based on spatial position. The method comprising: collecting images based on the high-definition image acquisition system; importing the image data and position information data into image processing software to create a mosaic image of each part of the bridge; importing the prepared spliced image map into the bridge disease intelligent identification system; obtaining the corresponding position and bridge of the bridge disease in the three-dimensional model of the bridge; identifying the stitched image map to obtain the size of the disease after identifying the bridge disease image and locating the bridge disease. The high-precision intelligent detection method for bridge diseases based on spatial position realizes automatic collection and intelligent analysis of bridge inspection data, reduces the workload of the inspection technicians and improves the detection efficiency.

Abstract: Embodiments described herein relate generally to a methodology of efficient object classification within a visual medium. The methodology utilizes a first neural network to perform an attention based object localization within a visual medium to generate a visual mask. The visual mask is applied to the visual medium to generate a masked visual medium. The masked visual medium may be then fed into a second neural network to detect and classify objects within the visual medium.

Abstract: A radio frequency module includes a first receive circuit that processes a receive signal in the first frequency band. The first receive circuit includes a first substrate, a first low noise amplifier, and a first filter circuit. The first low noise amplifier is mounted on a principal surface of the first substrate. The first filter circuit is connected to an output end of the first low noise amplifier. At least a portion of the first filter circuit is provided on the principal surface of the first substrate. The first filter circuit attenuates spurious components occurring due to a transmit signal in the first frequency band received by the first low noise amplifier. The spurious components are included in the transmit signal in the first frequency band and have a frequency bandwidth that overlaps, includes, or is included in the frequency bandwidth of the receive signal in the second frequency band.

Abstract: A computer-implemented method and system for connecting remote users with data gathered from a variety of apparatus: surveillance apparatus, identity confirmation apparatus, and drug testing apparatus to allow said remote users to know who is attempting to enter a given facility, whether a given person attempting entry to a given facility has or has not failed one or more drug tests, and what activity, such as drug use, is occurring at a given facility.

Abstract: Some embodiments are directed to a method to reinforce deep neural network learning capacity to classify rare cases, which includes the steps of training a first deep neural network used to classify generic cases of original data into specified labels; localizing discriminative class-specific features within the original data processed through the first deep neural network and mapping the discriminative class-specific features as spatial-probabilistic labels; training a second-deep neural network used to classify rare cases of the original data into the spatial-probabilistic labels; and training a combined deep neural network used to classify both generic and rare cases of the original data into primary combined specified and spatial-probabilistic labels.

Abstract: Embodiments of the present invention disclose a reference signal transmission method. A transmitting apparatus multiplies M first symbol sequences by M coefficients respectively to obtain M second symbol sequences, where M is a positive integer greater than 1, the symbol sequence includes L symbols, L is a positive integer greater than 1, and the M coefficients each have a magnitude of 1. The transmitting apparatus maps the M second symbol sequences onto a first time-frequency resource to obtain a frequency domain signal. The transmitting apparatus performs an IFFT operation on the frequency domain signal to obtain a time domain signal. And the transmitting apparatus sends the time domain signal.

Abstract: Techniques are described for crest factor reduction in power amplifier circuits. For example, crest factor reduction can keep the peak signal level of a signal for transmission to below a peak threshold level associated with a power amplifier in the transmission path. The signal is received by the crest factor reduction system and clipped in accordance with the peak threshold level. Edge smoothing is then applied to the clipped signal to reduce out-of-band emissions. The edge smoothing is implemented by a moving average filter, such as a time-domain box filter. In some embodiments, a maximum operation or minimum operation is used to prevent signal peak regrowth after the filtering. Some embodiments also include various iteration loops to further improve crest factor reduction.

Abstract: A computerized automated parameterization image pattern detection and classification method performs (1) morphological metrics learning using labeled region data to generate morphological metrics; (2) intensity metrics learning using learning image and labeled region data to generate intensity metrics; and (3) population learning using the morphological metrics and the intensity metrics to generate learned pattern detection parameter. The method may further update the learned pattern detection parameter using additional labeled region data and learning image, and apply pattern detection with optional user parameter adjustment to image data to generate detected pattern. The method may alternatively perform pixel parameter learning and pixel classification to generate pixel class confidence, and uses the pixel class confidence and the labeled region data to perform pattern parameter learning to generate the learned pattern detection parameter.

Abstract: Systems, methods, and processor readable media for distributing digital data and electrical power to a plurality of devices over high-impedance cables are disclosed. Certain embodiments include a gateway device connected to a power source, a first device connected to the gateway device by a cable, the cable being a high-impedance cable having at least two conductive paths, and wherein the first device receives electrical power and digital data from the gateway device via the cable over the same conductive path of the cable, a second device connected to the gateway device by the cable wherein the second device receives power and digital data from the gateway device via the cable over the same conductive path, and wherein the power source provides power to the first and second devices via the cable, and wherein the second device is connected to the gateway device through the first device via a daisy-chain topology.

Abstract: Embodiments described herein provide a system for facilitating entity recognition. During operation, a camera associated with a computing device captures at least a first image of a to-be-recognized entity under a first imaging condition. The system adjusts the first imaging condition to achieve a second imaging condition, and the camera captures at least a second image under the second imaging condition. The system determines whether the to-be-recognized entity is a physical entity based on the captured first and second images and the first and second imaging conditions.