Abstract: Various disclosed embodiments are directed to inpainting one or more portions of a target image based on merging (or selecting) one or more portions of a warped image with (or from) one or more portions of an inpainting candidate (e.g., via a learning model). This, among other functionality described herein, resolves the inaccuracies of existing image inpainting technologies.

Abstract: A computer readable recording medium storing at least one program, wherein an image pattern determining method for determining a stripe image can be performed when the program is executed. The image pattern determining method comprises: (a) classifying a single target image to a plurality of image blocks, wherein each of the image blocks comprises at least one pixel; (b) calculating pixel differences between pixel value sums of at least one of the image blocks and neighboring image blocks of the image block; (c) calculating image variation levels of each of the image blocks in a plurality of directions according to the pixel differences; and (d) determining whether the single target image comprises the strip image or not according to the image variation levels. An image pattern determining method for determining a check board image is also disclosed.

Abstract: A method for performing automatic visual inspection includes: capturing visual information of an object using a scanning system including a plurality of cameras; extracting, by a computing system including a processor and memory, one or more feature maps from the visual information using one or more feature extractors; classifying, by the computing system, the object by supplying the one or more feature maps to a complex classifier to compute a classification of the object, the complex classifier including: a plurality of simple classifiers, each simple classifier of the plurality of simple classifiers being configured to compute outputs representing a characteristic of the object; and one or more logical operators configured to combine the outputs of the simple classifiers to compute the classification of the object; and outputting, by the computing system, the classification of the object as a result of the automatic visual inspection.

Abstract: Aspects of the technology described herein relate to techniques for calculating, during imaging, a quality of a sequence of images collected during the imaging. Calculating the quality of the sequence of images may include calculating a probability that a medical professional would use a given image for clinical evaluation and a confidence that an automated analysis segmentation performed on the given image is correct. Techniques described herein also include receiving a trigger to perform an automatic measurement on a sequence of images, calculating a quality of the sequence of images, determining whether the quality of the sequence of images exceeds a threshold quality, and performing the automatic measurement on the sequence of images based on determining that the quality of the sequence of images exceeds the threshold quality.

Abstract: A computer-implemented method for computing a prediction on images of a scene includes: receiving one or more polarization raw frames of a scene, the polarization raw frames being captured with a polarizing filter at a different linear polarization angle; extracting one or more first tensors in one or more polarization representation spaces from the polarization raw frames; and computing a prediction regarding one or more optically challenging objects in the scene based on the one or more first tensors in the one or more polarization representation spaces.

Abstract: Methods and systems for characterizing holes in a combustor liner of a gas turbine engine, and associated repair methods are provided. One method comprises receiving first measured data of the combustor liner in an uncoated state. The method includes determining a first location and a first orientation of a first hole and a first location and a first orientation of a second hole in the combustor liner using the first measured data. The method includes receiving second measured data of the combustor liner in a coated state where the second hole is at least partially obstructed by a coating and the first hole is substantially unobstructed by the coating. The method includes inferring a second location of the second hole of the combustor liner in the coated state using a known spacing between the first location of the first hole and the first location of the second hole. The characterization of the holes may be used to re-drill the obstructed second hole.

Abstract: Systems and methods herein describe a metadata verification system that is configured to access a digital satellite image, generate a first discrete Fourier transform (DFT) pattern based on an ortho-rectified digital satellite image, generate a second DFT pattern based on rational polynomial coefficient (RPC) data of the digital satellite image, compare the first DFT pattern to the second DFT pattern, generate a score based on the comparison, and generate a determination of whether the digital satellite image has been manipulated based on the score.

Abstract: A device may receive complex data from a user device and may provide multiple images to the user device based on receiving the complex data. The device may receive, from the user device, a selection of two or more images from the multiple images, and may determine whether a combination of the two or more images is stored in a data structure. The device may determine a mapping of information identifying the two or more images with the complex data, based on the combination of the two or more images not being stored in the data structure, and may store the information identifying the two or more images, the complex data, and the mapping in the data structure. The device may process the two or more images to generate a reference image that satisfies a memorability score threshold and may provide the reference image to another user device.

Abstract: Provided are an image blur correcting device that capable of improving a degree of freedom in design and realizing miniaturization or weight reduction, a lens device including the image blur correcting device, and an imaging device including the lens device. An image blur correcting device includes a fixing member, a first movable member that is supported by the fixing member in a state of being movable in a direction X, and a second movable member that is supported by the first movable member in a state of being movable in a direction Y A second coil that drives the second movable member is fixed to one first surface of the second movable member in a direction Z, and a first coil that drives the first movable member is fixed to the other second surface of the second movable member in the direction Z.

Abstract: A computer-implemented method for auto-splitting and classifying an input document into one or more sub-documents using a machine learning system is described. The machine learning system includes a visual splitting neural network, an optical character recognition sub-system, a title classifier, a document classifier, and a grouper sub-system. The method includes: receiving a visual input representing a plurality of pages of the input document; classifying, using the visual splitting neural network, each page of the input document into a respective template of a plurality of templates; for each page of the input document, determining a final document type that the page belongs to; and grouping, using a grouper sub-system, the plurality of pages of the input document into one or more sub-documents based on (i) the respective template of each page and (ii) the respective final document type that each page belongs to.

Abstract: The present application discloses an image optimization method and system based on artificial intelligence, comprising: performing image object recognition for a template image, and extracting and recording template information of the template image; identifying the number and categories of primary objects in a to-be-optimized image by using an image recognition algorithm of a neural network; performing matching in a template database for the to-be-optimized image according to a set matching condition and the recorded template information to obtain optimal template information; scaling the primary object in the to-be-optimized image according to layout information in the optimal template information; cropping and adjusting a background part of the to-be-optimized image according to resolution requirements of an output target image and a basic composition principle; combining an image of the processed primary object with a background image according to the layout information in the optimal template information

Abstract: The techniques described herein relate to a systems and methods for a digital asset generation platform. The digital asset generation platform may ingest an ingest input. The digital asset generation platform may utilize a document identification engine corresponding to a first stage of a multi-stage convolutional neural network for identifying document types of documents. The digital asset generation platform may utilize an object detector engine corresponding to a second stage of the multi-stage convolutional neural network for detecting a dynamic mapping in the digital file. The digital asset generation platform may utilize a post-processing engine for classifying the dynamic mapping in the at least one digital file. The digital asset generation platform may dynamically generate a digital asset representative of the document based on the key value data pairs extracted from the dynamic mapping.

Abstract: Various methods and systems are provided for bicuspid valve detection with ultrasound imaging. In one embodiment, a method comprises acquiring ultrasound video of a heart over at least one cardiac cycle, identifying frames in the ultrasound video corresponding to at least one cardiac phase, and classifying a cardiac structure in the identified frames as a bicuspid valve or a tricuspid valve. A generative model such as a variational autoencoder trained on ultrasound image frames at the at least one cardiac phase may be used to classify the cardiac structure. In this way, relatively rare occurrences of bicuspid aortic valves may be automatically detected during regular cardiac ultrasound screenings.

Abstract: Disclosed are a system and method for quantifying changes in animal posture from video recordings of multiple interacting animals. Also disclosed are a system and method for training a posture identification algorithm efficiently with minimal human effort and evaluating the posture of millions of animal images. The disclosed process employs video recordings of behaving animals to produce a full set of geometrical coordinates for each body part over time. Inter alia, the disclosed system should be useful for organizations interested in doing large small-molecule screens to find drugs that affect the behavior of animals, and for those investigating new behavioral diagnostics for human patients. The disclosed system allows one to record video of animals and then automatically calculate the position of each body part over time. The output of this calculation can be used for simple analysis of the amount of movement for specific body parts, or part of a more complex scheme for measuring behaviors.

Abstract: Systems and methods for evaluating the physical and/or cosmetic condition of electronic devices using machine learning techniques are disclosed. In one example aspect, an example system includes a kiosk that comprises an inspection plate configured to hold an electronic device, one or more light sources arranged above the inspection plate configured to direct one or more light beams towards the electronic device, and one or more cameras configured to capture at least one image of a first side of the electronic device. The system also includes one or more processors in communication with the one or more cameras configured to extract a set of features of the electronic device and determine, via a first neural network, a condition of the electronic device based on the set of features.

Abstract: This method for inter-predictive encoding of a time-varying 3D point cloud including a series of successive frames divided in 3D blocks into at least one bitstream comprises encoding (20) 3D motion information including a geometric transformation comprising rotation information representative of a rotation transformation and translation information representative of a translation transformation, wherein the translation information comprises a vector ?T representing an estimation error of the translation transformation.

Abstract: The present disclosure provides a copy area identification method and device, which relates to the technical field of image processing. A copy area identification method according to the present disclosure includes: extracting feature information of multiple layers from an image to be processed; encoding the feature of the multiple layers information respectively, and jointly decoding according to encoded information of the multiple layers to acquire a jointly decoded output; acquiring information of pixels according to the jointly decoded output, wherein the information of the pixels comprises rotation angle information of the copy area, and a distance between each of the pixels and a border of the copy area; and determining a position of a border of the copy area according to the information of the pixels.

Abstract: An electronic apparatus includes a memory configured to store a plurality of images; and a processor configured to identify qualities of the plurality of images, process the plurality of images using at least one artificial intelligence model corresponding to the identified qualities, and obtain a graphic image including the processed plurality of images, and the at least one artificial intelligence model is trained to increase a quality of an input image.

Abstract: Systems and methods for digital image processing are described. Embodiments of the systems and methods includes identifying a digital image that includes an obscured region; generating a predicted image using a neural network comprising an encoder, a feature transfer network, and a decoder, wherein the feature transfer network is trained to predict features corresponding to the obscured region based on an output of the decoder; and combining the digital image and the predicted image to produce a reconstructed version of the digital image including details corresponding to the obscured region that are not present in the digital image.

Abstract: A depth image generation method includes obtaining a first depth image, based on a binocular image, obtaining a second depth image, using a depth camera, and obtaining a final depth image by performing image fusion on the obtained first depth image and the obtained second depth image.