A method, apparatus, and a non-transitory computer-readable storage medium for image denoising. The method may include obtaining a raw image captured by a camera. The method may also include obtaining a color modeled image based on the raw image. The method may further include obtaining a subsampled raw image based on the raw image. The method may also include obtaining a denoised image based on a neural network processing the color modeled image and the subsampled raw image.

A system and method of obtaining a quantitative evaluation of paper. By looking at the topographic data and comparing it to machine parameters, an operator can optimize the paper forming machine settings to create consistently high quality paper with minimal surface defects.

The present disclosure provides a mobile terminal comprising: a frame which is expanded in a first direction or is contracted in a second direction which is a reverse direction of the first direction; a display unit which is provided on one surface of the frame and includes: a screen expanded or contracted in correspondence to the expansion or contraction of the frame; a camera for obtaining an image corresponding to a specific angle of view; and a control unit for controlling, when the screen is expanded in the first direction, the display unit to output an image which continues in the first direction, on the expanded screen.

The present invention provides a method of angiography for cerebrovascular obliteration includes: using a classifier to obtain a 2D medical image using from a plurality of Multiphase CTA images; using a gray-scale conversion to obtain a N*M pixels grayscale image; filtering the grayscale image not being meet a condition of grayscale threshold and performing an image binarization to obtain a binarized image; confirming at least one vascular region and performing an image skeletonization; filtering according to a vascular image features of a vascular region to obtain a vascular-enhanced image; using a fracture analysis to obtain an analysis report related to a plurality of quantifying parameters of vascular characteristics; wherein the quantifying parameters of vascular characteristics comprises a quantitative value of fractal dimension (FD), vessel density (VD), skeleton density (SD) and vascular diameter index (VDI). Therefore, improve the accuracy of clinician diagnosis and the survival rates of patients with ischemic stroke

In one embodiment, a method includes receiving, by a defect detector module, an image of a physical object and classifying, by the defect detector module, one or more first features from the image of the physical object into one or more first classifications using one or more machine learning algorithms. The method further includes analyzing, by the defect detector module, the one or more first classifications and determining, by the defect detector module, that the physical object comprises a defect based on analyzing the one or more first classifications.

Systems and/or techniques for facilitating image forgery detection via headpose estimation are provided. In various embodiments, a system can receive a document from a client device. In various cases, the system can identify, by executing a first trained machine learning model, an object that is depicted in the document. In various instances, the system can determine, by executing a second trained machine learning model, a pose of the object. In various aspects, the system can determine, by executing a third trained machine learning model, whether the document is authentic or forged based on the pose of the object. In various embodiments, the system can, in response to determining that the document is forged, transmit an unsuccessful validation message to the client device.

In a multi-channel video mode, an electronic device may separately display a plurality of images from different cameras in a plurality of areas of a viewfinder frame. An image from one camera is displayed in one area, and a user operation such as a leftward sliding operation or a rightward sliding operation of a user in an area may be detected, to change framing presented by a corresponding camera in the area, without changing framing of another camera in a corresponding area. In this way, during multi-channel video recording, the user can separately adjust framing presented by each working camera in a preview frame, so that framing of each working camera in the preview frame does not affect each other, to avoid a problem that a change of framing of a working camera in the preview frame causes a change of framing of another working camera in the preview frame.

According to the present application, a computer-implemented method of predicting thyroid eye disease is disclosed. The method comprising: preparing a conjunctival hyperemia prediction model, a conjunctival edema prediction model, a lacrimal edema prediction model, an eyelid redness prediction model, and an eyelid edema prediction model, obtaining a facial image of an object, obtaining a first processed image and a second processed image from the facial image, wherein the first processed image is different from the second processed image, obtaining predicted values for each of a conjunctival hyperemia, a conjunctival edema and a lacrimal edema by applying the first processed image to the conjunctival hyperemia prediction model, the conjunctival edema prediction model, and the lacrimal edema prediction model, and obtaining predicted values for each of an eyelid redness and an eyelid edema by applying the second processed image to the eyelid redness prediction model and the eyelid edema prediction model.

An electronic device according to various embodiments of the disclosure may include: a camera module including a camera, a memory, and at least one processor electrically connected to the camera module and the memory, wherein the at least one processor may be configured to: successively obtain a plurality of first images through the camera module, align the plurality of first images, obtain a reference image based on the plurality of aligned first images, and obtain a second image using an artificial intelligence model based on the plurality of aligned first images and the reference image.

An apparatus including a capture device and a processor. The capture device may be configured to generate a plurality of video frames corresponding to users of a vehicle. The processor may be configured to perform operations to detect objects in the video frames, detect users of the vehicle based on the objects detected in the video frames, determine a limitation profile for the users, monitor for conditions provided by the limitation profile and generate a reaction if one or more of the conditions are met. The limitation profile may be determined in response to characteristics of the users. The characteristics of the users may be determined by performing the operations on each of the users.