Abstract: An image decoding method, according to the present invention, includes the steps of: deriving an MPM candidate mode from neighboring blocks adjacent to a target block to be decoded; generating an MPM list using the MPM candidate mode derived from the neighboring blocks; and deriving an intra prediction mode for the target block to be decoded using the generated MPM list. According to the present invention, image compression efficiency can be improved.

Abstract: A display panel, an electronic apparatus, and an imaging method of a display panel are provided. The display panel at least includes: an interface layer, at an outermost side of the display panel and configured to function as an interface between the display panel and ambient environment; a photosensitive layer, inside the display panel and below the interface layer; and a light-shielding layer, inside the display panel and between the interface layer and the photosensitive layer, the light-shielding layer being provided with a hole array which has a plurality of holes arranged in an array. The photosensitive layer is configured to acquire at a plurality of hole imaging areas respective images formed respectively therein.

Abstract: Provided are a fingerprint identification apparatus and an electronic device. The fingerprint identification apparatus is applied to an electronic device having a display screen, wherein the fingerprint identification apparatus comprises: a support plate; and at least one fingerprint sensor chip, wherein a middle frame of the electronic device is provided with a groove located on an upper surface, and the at least one fingerprint sensor chip is disposed in the groove of the middle frame through the support plate so that the at least one fingerprint sensor chip is located under the display screen of the electronic device. In embodiments of the present application, by the support plate, costs and complexity of an electronic device could be reduced, and maintainability could be improved.

Abstract: A texture image compensation method, a texture detection method and a device, and an electronic device are provided. The texture detection method includes: performing an image difference calculation on a first texture image acquired by a texture detection device and a foreign object correction image acquired by the texture detection device to compensate foreign object information in the first texture image, and to acquire a second texture image; performing and the texture detection by using the second texture image.

Abstract: Embodiments of the present disclosure provide a method and apparatus for processing a fundus image. The method may include: acquiring a target fundus image; dividing the target fundus image into at least two first image blocks; inputting a first image block into a pre-trained deep learning model, to obtain a first output value; and determining, based on the first output value and a threshold, whether the first image block is the fundus image block containing a predetermined type of image region.

Abstract: Aspects of the subject disclosure may include, for example, applying a model to a first unlabeled traffic item to generate a classification of the first unlabeled traffic item as a first class of traffic items or a second class of traffic items, generating a first score that is representative of a first confidence of the classification, determining that the first score is greater than a first threshold, and responsive to determining that the first score is greater than the first threshold, refining the model in accordance with at least the classification, resulting in a modified model. Other embodiments are disclosed.

Abstract: Provided are a fingerprint identification apparatus and an electronic device, and the fingerprint identification apparatus is applied to an electronic device having a display screen. The fingerprint identification apparatus comprises: a support plate used to fixedly connect with a middle frame of the electronic device; and at least one fingerprint sensor chip disposed on an upper surface of the support plate and disposed under the display screen through the support plate; wherein the at least one fingerprint sensor chip is configured to receive a fingerprint detecting signal returned by reflection or scattering via a human finger on the display screen, wherein the fingerprint detecting signal is used to detect fingerprint information of the finger.

Abstract: A method implements an activity protocol that has been established for a living entity. The method directs an artificial intelligence system to compare a video of an activity by a living entity to an activity protocol that has been established for the living entity, and then receives an indication from the artificial intelligence system that the activity by the living entity does not match the activity protocol that has been established for the living entity. In response to receiving the indication from the artificial intelligence system that the activity by the living entity does not match the activity protocol that has been established for the living entity, the method directs a monitoring entity to implement the activity protocol that has been established for the living entity.

Abstract: The disclosure relates to a system and method for correcting inhomogeneity in an MRI image. The method may include the steps of: acquiring a first set of k-space data, acquiring a second set of k-space data, generating the convolution kernel of the first set of k-space data based on the first set of k-space data and the second set of k-space data, performing inverse Fourier transform on the convolution kernel of the first set of k-space data to obtain an inversely transformed convolution kernel of the first set of k-space data, and generating a corrector based on the inversely transformed convolution kernel of the first set of k-space data. The method may be implemented on a machine including at least one processor and storage.

Abstract: A fingerprint sensor device with built-in liveness detection capabilities includes: an area sensor disposed on a top surface of a substrate; a stiffener disposed below a bottom surface of the substrate; a printed circuit making electrical connection to the sensor disposed below the stiffener; and a light source and a photodetector. At least one of the light source and photodetector is disposed on the printed circuit below the area sensor. The stiffener includes at least one through-hole located with respect to the light source or photodetector to allow light from the light source to transmit through the stiffener towards a finger located on the area sensor or to allow light reflected from the finger to pass through the stiffener to the photodetector.

Abstract: A fast object detection method and a fast object detection apparatus using an artificial neural network. The fast object detection method includes obtaining an input image; inputting the obtained input image into an object detection neural network using a plurality of preset bounding boxes; and detecting an object included in the input image by acquiring output data of the object detection neural network.

Abstract: A method for determining an impact score for a digital image includes providing the digital image wherein the digital image includes faces; using a processor to determine an image feature for the faces; using the processor to compute an object impact score for the faces, wherein the object impact score is based at least upon one of the determined image features; weighting the object impact score for the faces based on one of the determined image features for a face; using the processor to compute an impact score for the digital image by combining the weighted object impact scores for the faces in the image; and storing the computed impact score in a processor accessible memory.

Abstract: Systems and methods for detecting, counting and analyzing the blood content of a surgical textile are provided, utilizing an infrared or depth camera in conjunction with a color image.

Abstract: A computer-program product storing instructions which, when executed by a computer, cause the computer to receive an input data, encode the input via an encoder, during a first sequence, obtain a first latent variable defining an attribute of the input data, generate a sequential reconstruction of the input data utilizing the decoder and at least the first latent variable, obtain a residual between the input data and the reconstruction utilizing a comparison of at least the first latent variable, and output a final reconstruction of the input data utilizing a plurality of residuals from a plurality of sequences.

Abstract: An autonomous system for generating and interpreting point clouds of a rail corridor along a survey path while moving on a railroad corridor assessment platform. The system includes two rear-facing LiDAR sensors configured to scan along scan planes that intersect but not at all points. The system also includes a plurality of high-resolution cameras for gathering image data from a rail corridor. The LiDAR sensors and the high-resolution cameras are housed in autonomously controlled and temperature controlled protective enclosures.

Abstract: A method for determining a finger motion on a fingerprint sensor comprising a sensing area, the method comprises: receiving a finger on the sensing area of the fingerprint sensor; when an amount of sensor area coverage caused by the finger touching the sensing area is below a coverage threshold, acquiring images of a first type using a first image acquisition setting with the fingerprint sensor, when the amount of sensor area coverage is equal to or exceeds the coverage threshold, acquiring images of a second type using a second image acquisition setting with the fingerprint sensor, and determining a present motion of the finger on the fingerprint sensor based on the first type of images or the second type of images depending on a present amount of sensor area coverage.

Abstract: A touch-fingerprint complex sensor includes a fingerprint substrate provided in a fingerprint area and a touch area, common electrodes provided above the fingerprint substrate in a direction that is normal to an upper surface of the fingerprint substrate, fingerprint electrodes provided between the fingerprint substrate and the common electrodes in the direction, and touch electrodes provided below the common electrodes and the fingerprint substrate in the direction, wherein a first subset of the common electrodes, and the fingerprint electrodes are provided in the fingerprint area, and a second subset of the common electrodes, and the touch electrodes are provided in the touch area.

Abstract: A display device includes a transparent display panel, which includes a display area, the display area having a fingerprint recognition region; a rear surface film attached to the rear surface of the transparent display panel and having a through-hole corresponding to the fingerprint recognition region; a fingerprint sensor in the through-hole; and a photochromic part overlapping the through-hole.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating video frames using neural networks. One of the methods includes processing a sequence of video frames using an encoder neural network to generate an encoded representation; and generating a predicted next frame pixel by pixel according to a pixel order and a channel order, comprising: for each color channel of each pixel, providing as input to a decoder neural network (i) the encoded representation, (ii) color values for any pixels before the pixel in the pixel order, and (iii) color values for the pixel for any color channels before the color channel in the channel order, wherein the decoder neural network is configured to generate an output defining a score distribution over a plurality of possible color values, and determining the color value for the color channel of the pixel by sampling from the score distribution.

Abstract: The present disclosure relates to a system. The system may obtain a k-space dataset according to magnetic resonance (MR) signals acquired by a magnetic resonance imaging (MRI) scanner. The system may also generate, based on the k-space dataset using an image reconstruction model that includes a sequence sub-model and a domain translation sub-model, a reconstructed image by: inputting at least a part of the k-space dataset into the sequence sub-model; outputting, from the sequence sub-model, a feature representation of the k-space dataset; inputting the feature representation of the k-space dataset into the domain translation sub-model; and outputting, from the domain translation sub-model, the reconstructed image.