Abstract: Automated inventory management and material (or container) handling removes the requirement to operate fully automatically or all-manual using conventional task dedicated vertical storage and retrieval (S&R) machines. Inventory requests Automated vehicles plan their own movements to execute missions over a container yard, warehouse aisles or roadways, sharing this space with manually driven trucks. Automated units drive to planned speed limits, manage their loads (stability control), stop, go, and merge at intersections according human driving rules, use on-board sensors to identify static and dynamic obstacles, and human traffic, and either avoid them or stop until potential collision risk is removed. They identify, localize, and either pick-up loads (pallets, container, etc.) or drop them at the correctly demined locations. Systems without full automation can also implement partially automated operations (for instance load pick-up and drop), and can assure inherently safe manually operated vehicles (i.

Abstract: Evaluating dose performance of a radiographic imaging system with respect to image quality using a phantom, a channelized hotelling observer module as a model observer, and a printer, a plaque, or an electronic display includes scanning and producing images for a plurality of sections of the phantom using the radiographic imaging system, wherein the plurality of sections represent a range of patient sizes and doses and wherein the sections of the phantom contain objects of measurable detectability. Also included is analyzing the images to determine detectability results for one or more of the contained objects within the images of the plurality of sections of the phantom, wherein the analyzing includes using a channelized hotelling observer (CHO) module as a model observer; and displaying, via the printer, the plaque, or the electronic display, a continuous detectability performance measurement function using the determined detectability results.

Abstract: Motion contaminated magnetic resonance (MR) images for training an artificial neural network to remove motion artifacts from the MR images are difficult to obtain. Described herein are systems, methods, and instrumentalities for injecting motion artifacts into clean MR images and using the artificially contaminated images for machine learning and neural network training. The motion contaminated MR images may be created based on clean source MR images that are associated with multiple physiological cycles of a scanned object, and by deriving MR data segments for the multiple physiological cycles based on the source MR images. The MR data segments thus derived may be combined to obtain a simulated MR data set, from which one or more target MR images may be generated to exhibit a motion artifact. The motion artifact may be created by manipulating the source MR images and/or controlling the manner in which the MR data set or the target MR images are generated.

Abstract: A training data generation device performs the processes of: acquiring first correct answer data that is correct answer data with respect to each training image of a training image group, the training image group including plural training images to be given the correct answer data, the training image group being divided into plural image subgroups, the first correct answer data being generated in a different situation for each of the plural image subgroups; generating a discriminator with respect to the each of the plural image subgroups, the discriminator being learned based on the each of the plural image subgroups and the first correct answer data corresponding to the each of the plural image subgroups; acquiring a discrimination result outputted by the discriminator for each of the plural training images by inputting the each of the plural training images to the discriminator which is generated based on at least one image subgroup other than an image subgroup to which the each of the training images belon

Abstract: Apparatus, systems and methods for adaptively reducing blocking artifacts in block-coded video are disclosed. In one implementation, a system includes processing logic at least capable of deblock filtering at least a portion of a line of video data based, at least in part, on edge information and texture information to generate at least a portion of a line of deblocked video data, and an image data output device responsive to the processing logic.

Abstract: An imaging system includes a light source to emit a plurality of wavelengths of light, and a camera coupled to receive the light reflected back from tissue in a body. Also included are a database with reflectance data for a plurality of tissue types, and a controller coupled to the light source, the database, and the camera. The controller causes the imaging system to perform operations, including: generating image data with the camera; receiving the image data from the camera with the controller; comparing, with the controller, the image data to the reflectance data in the database; and determining a tissue type in the image data in response to comparing the image data to the reflectance data.

Abstract: In various examples, systems and methods are disclosed that preserve rich spatial information from an input resolution of a machine learning model to regress on lines in an input image. The machine learning model may be trained to predict, in deployment, distances for each pixel of the input image at an input resolution to a line pixel determined to correspond to a line in the input image. The machine learning model may further be trained to predict angles and label classes of the line. An embedding algorithm may be used to train the machine learning model to predict clusters of line pixels that each correspond to a respective line in the input image. In deployment, the predictions of the machine learning model may be used as an aid for understanding the surrounding environment—e.g., for updating a world model—in a variety of autonomous machine applications.

Abstract: Systems, apparatuses, and methods for scanning a shopping space. The system pace comprises a locomotion system of a motorized unit, a camera system, and a central computer system. The central computer system is configured to receive motorized unit location information from the locomotion system, the motorized unit location information comprises a plurality of sets of coordinates each associated with a timestamp, receive item identifier instances from the camera system, wherein each item identifier instance is associated with a timestamp, and determine a location for each item identifier instance based on the timestamps associated of the item identifier instances and the timestamps associated with the plurality of sets of coordinates of the motorized unit location information.

Abstract: This video signal processing apparatus includes a signal processing unit that performs tone control on an input video signal having a linear characteristic and a control unit that blends two tone curve characteristics arbitrarily selected from among a plurality of tone curve characteristics prepared in advance and sets the blended tone curve characteristics for the tone control of the signal processing unit.

Abstract: A method is provided. The method includes: reading video information of a 3D video to be rendered; determining an image format of the 3D video according to the video information; generating a first spherical model and a second spherical model according to the image format; reading a frame image of the 3D video, where the frame image includes a first sub-image and a second sub-image; obtaining angle-of-view rotation data and image sealing data; rendering the frame image according to the angle-of-view rotation data and the image scaling data, where the first sub-image is rendered to the first spherical model to obtain a first spherical image, and the second sub-image is rendered to the second spherical model to obtain a second spherical image; and outputting images in a viewport area of the first spherical image and the second spherical image to a display device.

Abstract: An image correction method includes: acquiring band images obtained by imaging a subject, and a high-resolution image having a resolution higher than that of the band images; acquiring a position difference between the object band image and the reference band image among the band images; by using a pixel of the object band image as an object pixel, for each object pixel, determining a pixel value of each sub-region obtained by dividing the imaging region of the object pixel into a plurality of regions, based on the pixel value of the object pixel and a relationship between pixel values of the pixels of the high-resolution image corresponding to the object pixel; and creating a corrected band image that holds a pixel value of light on the object band image at the pixel position of the reference band image, from the determined pixel value of each sub-region and the position difference.

Abstract: Disclosed are a codebook processing method, a terminal device, and a network device, the method comprising: determining weighting coefficients for codebook calculation based on a first number and a second number, wherein a value of L representing the first number is half of a number of spatial beams, a value of M representing the second number is a number of discrete fourier transform (DFT) basis vectors. L and M are both integers, and the weighting coefficients comprise amplitude coefficients; performing processing on the weighting coefficients; and transmitting the processed weighting coefficients to a network device through channel state information (CSI).

Abstract: A sky filter method for panoramic images and a portable terminal is provided. The method comprises: obtaining several panoramic images containing sky regions as a data set, and marking a sky region and a ground region of each panoramic image to obtain a marked mask image and a panoramic template image of sky; extracting features of the sky region and the ground region of each panoramic image, and marking a positive sample and a negative sample; inputting the positive sample and the negative sample to SVM for training to obtain a model; extracting the features of the panoramic images, and inputting same to the model to obtain an initial mask image; removing a misclassified pixel and a misclassified region in the initial mask image to obtain an accurate mask image; and fuse the panoramic template image of sky and a test panoramic image to achieve a sky filter effect.

Abstract: The present invention relates to a deep-learning based system and method of automatically determining a degree of damage to each area of a vehicle, which is capable of quickly calculating a consistent and reliable quote for vehicle repair by analyzing an image of a vehicle in an accident by using a deep learning-based Mark R-CNN framework and then extracting a component image corresponding to a damaged part, and automatically determining the degree of damage in the extracted component image based on a pre-trained model.

Abstract: Embodiments for training a deep neural network by applying tags to enhanced versions of a raw data set are disclosed. In one embodiment, the raw data set may comprise, for example, images, and the method may comprise receiving the raw data set of images, applying an enhancement to the images, deriving tags based on the enhanced images while maintaining a correlation to the original raw images, and using the raw images and the tags to train a deep neural network.

Abstract: A method of training a fingerprint image enhancing engine for use in a fingerprint capturing device, and a corresponding apparatus and computer readable medium, include producing a synthetic image dataset comprising plural pairs of synthetic images. Each pair of synthetic images include a clean synthetic image and a raw synthetic image corresponding to the clean synthetic image. Each raw synthetic image is produced according to a model of the fingerprint capturing device. The method also includes training a neural network using the synthetic image dataset.

Abstract: A method of generating information to control display of images providing a display device with align pattern data to which box data having a maximum reference gray level is added, obtaining a first capture image generated based on the align pattern data to which the box data is added, providing the display device with one or more full pattern data respectively having one or more reference gray levels lower than the maximum reference gray level, and obtaining one or more second capture images generated based on the one or more full pattern data. The method also includes generating compensation data including compensation values at the one or more reference gray levels and the maximum reference gray level. The compensation data may be generated based on the one or more second capture images and a portion of the first capture image corresponding to the box data.

Abstract: An apparatus for edge aware upscaling is described herein. The apparatus comprises a potential edge detector, a thin-edge detector, a one-directional edge detector, a correlation detector, and a corrector. The potential edge detector identifies potential edge pixels in an input image, and the thin-edge detector detects thin edges in the potential edge pixels of the input image. The one-directional edge detector detects one-directional edges in the potential edge pixels of the input image, and the correlation detector detects strongly correlated edges in the potential edge pixels of the input image. The corrector derives a target output value based on an edge type and classification of a corresponding input pixel as identified by a source map point.

Abstract: Embodiments are disclosed for automatic object re-colorization in images. In some embodiments, a method of automatic object re-colorization includes receiving a request to recolor an object in an image, the request including an object identifier and a color identifier, identifying an object in the image associated with the object identifier, generating a mask corresponding to the object in the image, providing the image, the mask, and the color identifier to a color transformer network, the color transformer network trained to recolor objects in input images, and generating, by the color transformer network, a recolored image, wherein the object in the recolored image has been recolored to a color corresponding to the color identifier.

Abstract: A method includes the following steps: pre-processing chest X-ray films to obtain initial X-ray film images that meets format requirements; screening the initial X-ray film images to detect whether they are posteroanterior chest images; inputting the posteroanterior chest images into a binary classification model of the deep convolutional neural network for negative and positive classification; inputting the images presenting positive results into a detection model of the deep convolutional neural network to detect a disease type and label an outline of a lesion area in each image; and displaying the disease type and lesion area corresponding to the image.

Abstract: Disclosed are a signal processing device and an image display apparatus including the same. The signal processing device of an embodiment of the present disclosure includes: a quality calculator configured to calculate a source quality of an image signal received from an external settop box or a network; an image quality setter configured to set an image quality of the image signal based on the calculated source quality; and an image quality processor configured to perform image quality processing on the image signal based on the set image quality, wherein in response to the source quality of the received image signal being changed at a first time point, the image quality setter changes an image quality setting sequentially from a first setting to a second setting; and based on the image quality setting, the image quality processor performs image quality processing. Accordingly, flicker may be reduced when an image quality is changed due to a change in the source quality of the received image signal.

Abstract: An image processing device includes an image acquisition unit that acquires a captured image to be processed from a storage unit in which a captured image having first date/time information indicating a time of imaging is stored, a date/time information acquisition unit that acquires the first date/time information and acquires second date/time information indicating a date/time when the captured image to be processed is acquired, an elapsed date/time calculation unit that calculates an elapsed date/time from the time of imaging by making a comparison between the first date/time information and the second date/time information, and an image processing unit that selects image processing based on a length of the elapsed date/time from among a plurality of kinds of image processing that change according to the length of the elapsed date/time and performs the selected image processing on the captured image to be processed.

Abstract: A system or process may generate a summarization of multimedia content by determining one or more salient moments therefrom. Multimedia content may be received and a plurality of frames and audio, visual, and metadata elements associated therewith are extracted from the multimedia content. A plurality of importance sub-scores may be generated for each frame of the multimedia content, each of the plurality of sub-scores being associated with a particular analytical modality. For each frame, the plurality of importance sub-scores associated therewith may be aggregated into an importance score. The frames may be ranked by importance and a plurality of top-ranked frames are identified and determined to satisfy an importance threshold. The plurality of top-ranked frames are sequentially arranged and merged into a plurality of moment candidates that are ranked for importance. A subset of top-ranked moment candidates are merged into a final summarization of the multimedia content.

Abstract: An method and an apparatus for generating an image, and an electronic device are provided. The method comprises: performing a plurality of types of image enhancement processing on an image to be processed respectively to obtain a plurality of pre-enhanced images; performing image quality classification on a first image block in the image to be processed to obtain a first quality classification result for the first image block; determining a target pre-enhanced image from the plurality of pre-enhanced images based on the first quality classification result for the first image block; determining a second image block in the target pre-enhanced image; and generating a target image based on the second image block.

Abstract: Systems, methods, apparatuses, and computer program products for providing multimodal emotion recognition. The method may include receiving raw input from an input source. The method may also include extracting one or more feature vectors from the raw input. The method may further include determining an effectiveness of the one or more feature vectors. Further, the method may include performing, based on the determination, multiplicative fusion processing on the one or more feature vectors. The method may also include predicting, based on results of the multiplicative fusion processing, one or more emotions of the input source.

Abstract: Innovations in flexible reference picture management are described. For example, a video encoder and video decoder use a global reference picture set (“GRPS”) of reference pictures that remain in memory, and hence are available for use in video encoding/decoding, longer than conventional reference pictures. In particular, reference pictures of the GRPS remain available across random access boundaries. Or, as another example, a video encoder and video decoder clip a reference picture so that useful regions of the reference picture are retained in memory, while unhelpful or redundant regions of the reference picture are discarded. Reference picture clipping can reduce the amount of memory needed to store reference pictures or improve the utilization of available memory by providing better options for motion compensation. Or, as still another example, a video encoder and video decoder filter a reference picture to remove random noise (e.g., capture noise due to camera imperfections during capture).

Abstract: A method of image processing in a structured light imaging system is provided that includes receiving a captured image of a scene, wherein the captured image is captured by a camera of a projector-camera pair, and wherein the captured image includes a binary pattern projected into the scene by the projector, applying a filter to the rectified captured image to generate a local threshold image, wherein the local threshold image includes a local threshold value for each pixel in the rectified captured image, and extracting a binary image from the rectified captured image wherein a value of each location in the binary image is determined based on a comparison of a value of a pixel in a corresponding location in the rectified captured image to a local threshold value in a corresponding location in the local threshold image.

Abstract: A solid-state imaging device includes: an imager (11) configured to acquire image data; a processing unit (14) configured to execute, on the image data or data based on the image data, processing of extracting a specific region based on a neural network calculation model; and an output unit (16) configured to output image data fabricated based on the specific region or the image data read from the imager based on the specific region.

Abstract: Apparatuses, systems, and techniques to perform effective tone management for image data. In an embodiment, a set of contrast gain curves are generated corresponding to a set of tonal ranges of an input image. An output image may then be generated by at least applying corresponding contrast gain curves to tonal ranges of the input image.

Abstract: Apparatuses, systems, and techniques are presented to generate images with one or more visual effects applied. In at least one embodiment, one or more visual effects are applied to one or more images having a resolution that is less than a first resolution and those visual effects approximated for one or more images having a resolution that is greater than or equal to the first resolution.

Abstract: The disclosure introduces a user authentication method Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA), the user authentication method including: determining a correct answer pattern having at least one correct answer direction; generating, with respect to each of the at least one correct answer direction, an animation of an arrow object rotating with a movement distinguished from movements in other directions with reference to the correct answer direction; displaying a CAPTCHA interface corresponding to the correct answer pattern and including an arrangement of the generated animation; receiving a direction input from a user; and determining whether the user has been authenticated according to a result of comparing the direction input with the correct answer pattern.

Abstract: Systems and methods to perform noise-adaptive non-blind deblurring on an input image that includes blur and noise involve implementing a first neural network on the input image to obtain one or more parameters and performing regularized deconvolution to obtain a deblurred image from the input image. The regularized deconvolution uses the one or more parameters to control noise in the deblurred image. A method includes implementing a second neural network to remove artifacts from the deblurred image and provide an output image.

Abstract: An embodiment of an image recording apparatus includes an eyeglass frame, at least one first optical unit disposed on the eyeglass frame for capturing a main scene image, and at least one second optical unit disposed on the eyeglass frame for capturing an auxiliary scene image. The first and the second field of view of the user at least partially overlap. The image resolution of the main scene image is lower than the image resolution of the main scene image and the field of view of the main scene image is larger than the field of view of the auxiliary scene image. The image recording apparatus further includes at least one processor for receiving the main and the auxiliary scene images, and generating a modified resolution copy of the main scene image based on the auxiliary scene image.

Abstract: An image processing apparatus with a processor and a memory storing instructions, that, when executed, cause the processor to obtain HDR data representing a high-dynamic range (HDR) image, in an image transfer function of the HDR data, a tone of each pixel is defined based on a relative luminance value, to obtain print information to perform printing based on the obtained HDR data, to set luminance information to be a target absolute luminance value, and to perform a luminance conversion on the HDR data so that a tone of each pixel is defined based on an absolute luminance value and the target absolute luminance value being a maximum luminance, to convert a dynamic range of luminance of the HDR data, on which the luminance conversion has been performed, into a dynamic range corresponding to printing of an image on a print medium performed based on the print information.

Abstract: A computer-implemented method is provided of finding one or more data items that match one or more defined criteria in a dataset. The method comprises identifying data snippets of the dataset using a set of one or more attention rules; categorizing the identified data snippets using fuzzy matching by assigning them to buckets such that each bucket contains data snippets that are similar to another according to a similarity measure; classifying buckets containing data snippets having more than a threshold number of the true positive data items as true positive buckets and remaining buckets as false positive buckets; calculating culling rules based on the true positive buckets and the false positive buckets, and using the culling rules to remove the false positive data items from the true positive buckets.

Abstract: Systems and methods are provided for analyzing messages generated by a plurality of computing devices associated with a plurality of users in a messaging system to generate training data to train a machine learning model to determine a probability that a media content item was generated inside an enclosed location or outside, receiving a media content item from a computing device, analyzing the media content item using the trained machine learning model to determine a probability that the media content item was generated inside an enclosed location or outside, determining, based on the probability generated by the trained machine learning model, that the media content item was generated inside an enclosed location, and determining an inside temperature associated with the venue based on messages generated by a plurality of computing devices in a messaging system comprising media content items and temperature information for the venue or a similar venue type.

Abstract: Embodiments of this disclosure include an image enhancement method and apparatus. The image enhancement may include obtaining an original image and performing synthesis processing on features of the original image to obtain a first illumination map corresponding to the original image. A resolution of the first illumination map may be lower than a resolution of the original image. The image enhancement may further include obtaining, based on the first illumination map, a mapping relationship between an image to an illumination map and performing mapping processing on the original image based on the mapping relationship to obtain a second illumination map. A resolution of the second illumination map may be equal to the resolution of the original image. The image enhancement may further include performing image enhancement processing on the original image according to the second illumination map to obtain a target image.

Abstract: The present disclosure discloses a method for reconstructing geostationary ocean color satellite data based on Data INterpolating Empirical Orthogonal Functions. The method includes steps of: 1) for an original ocean color remote sensing area, using concentration detection and edge detection to eliminate abnormal image elements; 2) in the Data INterpolating Empirical Orthogonal Functions, using Laplace smoothing filter to smoothly filter a time covariance matrix; 3) for temporal modes value obtained by the Data INterpolating Empirical Orthogonal Functions, first decomposing it into sub-temporal mode, then adopting empirical modal decomposition, and finally performing interpolation, to obtain an ocean color remote sensing reanalysis data set that maintains its original accuracy and full coverage of time and space.

Abstract: The present disclosure relates to an apparatus and method for optimizing inverse tone mapping on basis of a single image to reconstruct into a high quality High Dynamic Range (HDR) image using a Low Dynamic Range (LDR) image and a recording medium for performing the method, and includes inputting a LDR image to Inverse Tone Mapping (ITM) operator, inputting a result value by the ITM operator to Tone Mapping (TM) operator, comparing a result value by the TM operator with a threshold for HDR luminance determination, and selecting the result value by the TM operator which is smaller than the threshold as an HDR image.

Abstract: An imaging system includes a focal plane array, readout electronics, and a computing system in which the number of active pixels is either set at a low-fraction of the total pixels thereby reducing the effect of radiation damage, or radiation damage over time is detected and automatically compensated. Machine learning is used to identify radiation damaged pixels and damaged regions which are subsequently eliminated and replaced by the computational system. The machine learning is used to identify changes in the fixed pattern signal/noise and/or noise of the system, and is then computationally corrected.

Abstract: Embodiments of the present application provide a method and a device of inverse tone mapping and an electronic device. The method includes: obtaining one or more low dynamic range images; performing a decomposition operation to the low dynamic range image to acquire a detail layer and a basic layer of the low dynamic range image; restoring the detail layer and the basic layer by using a predetermined first restoration network and a second restoration network to acquire restored detail layer and basic layer; and adjusting the restored detail layer and basic layer by using a predetermined fusion network to acquire an adjusted high dynamic range image. With the technical solution of the present application, the conversion from a low dynamic range image to a high dynamic range image can be more robustly completed without complicated parameter settings.

Abstract: Devices, methods, and non-transitory program storage devices (NPSDs) for an improved, so-called “hybrid” image registration process are disclosed herein, comprising: obtaining a first set of captured images, wherein the first set of captured images comprises a reference image and one or more bracketed images; and for each of the one or more bracketed images: performing a first (e.g., global) registration operation and a second (e.g., dense, or other localized) registration operation on the bracketed image with respect to the reference image, wherein each of the first and second registration operations produces an output; generating a blend map for the bracketed image, wherein each value in the blend map indicates whether to use the first or second registration operation output for a corresponding one or more pixels when registering the bracketed image with the reference image; and registering the bracketed image with the reference image, according to the generated blend map.

Abstract: Medical imaging systems and methods for representing a 3D volume containing at least one foreign object introduced into a tissue. Imaging methods may include provision of a 3D volume containing voxels of at least one foreign object and voxels of tissue surrounding the at least one foreign object, identification of the voxels of the at least one foreign object by application of a processing rule, segmentation of the voxels of the at least one foreign object from the voxels of the tissue surrounding the at least one foreign object while maintaining the 3D volume, generation of a synthetic volume from a residual volume and the volume of the at least one foreign object, and representation of the synthetic volume on a display device using a windowing system.

Abstract: Techniques for emulating frequency coefficients of film grain for video (e.g., frame) encoding are described. According to some embodiments, a computer-implemented method includes receiving a request to encode a video with film grain at a content delivery service, performing a film grain synthesis on a frame of the video with film grain to generate film grain metadata for the frame and generate a degrained frame from the frame, determining film grain emulation frequency coefficients based at least in part on the film grain metadata for the frame, performing a frequency transform on the degrained frame to generate frequency coefficients for the degrained frame, encoding the frame into an encoded frame, by the content delivery service, based at least in part on the frequency coefficients for the degrained frame and the film grain emulation frequency coefficients, and transmitting the encoded frame from the content delivery service to a viewer device.

Abstract: Embodiments of a marine survey image enhancement system (MSIES) using temporal images from underwater camera are disclosed. In some embodiments, a MSIES system includes: a pre-processing module used to sub-sample input image into smaller image chunks; a DNN module constructed with many complex layers of neurons connected together and is designed to consume low quality, noisy image and produce high resolution realistic image; a post-processing module that merges all the output images from the DNN module with the original input image, forming a clearer, more detailed and higher signal to noise ratio marine survey image.

Abstract: A system is disclosed. The system includes at least one physical memory device to store calibration logic and one or more processors coupled with the at least one physical memory device to execute the calibration logic to receive an image having a blended input color comprising a first primary color value and a second primary color value, generate blend weights for the blended input color based on the first primary color value and the second primary color value, receive a plurality of transfer functions corresponding to each of the first primary color value and the second primary color values and apply the blend weights and the plurality of transfer functions to the first primary color value and the second primary color value to generate a uniformity corrected first primary color value and a uniformity corrected second primary color value associated with the blended input color.

Abstract: An information processing apparatus includes: a first preprocessing arithmetic device configured to execute preprocessing for analog data from a first sensor; and a first post-processing arithmetic device connected to the first preprocessing arithmetic device and configured to execute post-processing for first preprocessed data, wherein the first preprocessing arithmetic device includes a first processor configured to: receive the analog data from the first sensor and convert the analog data into digital data; output feature data on the basis of a result of execution of feature extraction processing for the digital data; and output the feature data, and the first post-processing arithmetic device includes a second processor configured to: input the feature data; store the feature data in a first memory; and store, in the first memory, recognition result data based on a result of execution of recognition processing for the feature data.

Abstract: A system and method include identification of a plurality of sub-volumes of an image volume, each of the plurality of sub-volumes of the image volume associated with a respective one of a plurality of vertebra, registration of each of the plurality of sub-volumes of the image volume to one of a plurality of reference sub-volumes associated with a same respective vertebra, input of the registered sub-volumes and the image volume to a trained neural network, reception of an output image volume from the trained neural network, the output image volume labeled to associate voxels with respective vertebra, and display of the output image volume.

Abstract: A method and system including: defining a geographic area; receiving a plurality of images; determining a plurality of image points; partitioning the geographic area into a plurality of image regions based on the plurality of image points; and stitching the plurality of images into a combined image based on the plurality of image regions.

Abstract: Techniques are described for automated analysis and use of images acquired of an object and of associated image acquisition metadata, such as for manmade largescale objects at fixed locations in outdoor environments, and to automatically generate a 3D computer model of the object (e.g., the 3D shape of the object exterior's surface) from visual data in the acquired images and from image acquisition device motion data during the image acquisition, to use the computer model to automatically determine measurements for object attribute(s), and to display or otherwise provide information about the generated computer model and/or determined object attributes. The image acquisition metadata may include motion data from IMU (inertial measurement unit) sensors on the image acquisition device, and include additional related data that is determined based at least in part on that motion data (e.g., acquisition pose data for particular acquired images, 3D positions on object exterior, etc.).