Abstract: Systems and methods for transfer-to-transfer training using an imbalanced training dataset include reconfiguring an imbalanced training data corpus to a plurality of distinct class-balanced mini-corpora of training data, wherein the reconfiguring includes: (i) partitioning the imbalanced training data corpus into a plurality of mini-corpora of training data samples in which each distinct mini-corpus of the plurality of mini-corpora includes an entirety of the training data samples within the second subset of training data samples; and (ii) allocating an equal number of the training data samples of the first subset into each of the plurality of mini-corpora of training data samples; and transfer-to-transfer learning-based training a subject machine learning algorithm to a trained machine learning model based on implementing the transfer-to-transfer learning-based training using the plurality of distinct class-balanced mini-corpora, wherein in use, the trained machine learning model predicts a presence or a non

Abstract: Disclosed embodiments provide systems, methods, and computer-readable storage media for stress testing a vehicle identification model by determining image quality parameters optimizing model confidence values. The embodiments comprise one or more memory devices storing instructions and one or more processors configured to execute instructions. The one or more processors perform operations comprising receiving a first set of images of the vehicle, wherein the images contain preset values for parameters comprising at least one of a rotation, a focus, a contrast, and a color. The system further analyzes the first set of images with an identification model and determining an initial identification confidence of the vehicle. The system further modifies the first set of images, compares the modified images to the first set of images, and determines whether the model should be modified based on at least the comparison.

Abstract: Method, terminal, and storage medium for tracking facial critical area are provided. The method includes accessing a frame of image in a video file; obtaining coordinate frame data of a facial part in the image; determining initial coordinate frame data of a critical area in the facial part according to the coordinate frame data of the facial part; obtaining coordinate frame data of the critical area according to the initial coordinate frame data of the critical area in the facial part; accessing an adjacent next frame of image in the video file; obtaining initial coordinate frame data of the critical area in the facial part for the adjacent next frame of image by using the coordinate frame data of the critical area in the frame; and obtaining coordinate frame data of the critical area for the adjacent next frame of image according to the initial coordinate frame data thereof.

Abstract: The disclosure relates to a method and an apparatus for analyzing an image using a deep neural net pre-trained for multiple classes. The image is processed by a forward pass through an adapted neural net to generate a processing result. The adapted neural net is adapted from the pre-trained neural net to focus on exactly one selected class. The processing result is then analyzed focused on features corresponding to the selected class using an image processing algorithm. A modified image is generated by removing a manifestation of these features from the image.

Abstract: A method of processing a mixed bunch of banknotes and checks in a recycling self-service terminal is described. The method comprises: receiving a bunch of documents; recognizing each document from the received bunch; for each banknote recognized from the received bunch, validating the authenticity of that banknote; for each check recognized from the received bunch, extracting financial information from that check; and notifying a customer of the total value of the deposited bunch. A document validator, and a self-service terminal including the document validator, are also described.

Abstract: The disclosure relates to a system and method for image reconstruction. The method may include the steps of: obtaining raw data corresponding to radiation rays within a volume, determining a radiation ray passing a plurality of voxels, grouping the voxels into a plurality of subsets such that at least some subset of voxels are sequentially loaded into a memory, and performing a calculation relating to the sequentially loaded voxels. The radiation ray may be determined based on the raw data. The calculation may be performed by a plurality of processing threads in a parallel hardware architecture. A processing thread may correspond to a subset of voxels.

Abstract: A method for using an assembled three-dimensional image to construct a three-dimensional model for determining a path through a lumen network to a target. The three-dimensional model is automatically registered to an actual location of a probe by tracking and recording the positions of the probe and continually adjusting the registration between the model and a display of the probe position. The registration algorithm becomes dynamic (elastic) as the probe approaches smaller lumens in the periphery of the network where movement has a bigger impact on the registration between the model and the probe display.

Abstract: A system, method and program product for implementing a sparse sampling strategy for acquiring MRI data. A method includes: collecting and labeling a training dataset of MRI scans for a predetermined diagnostic; selecting a sampling shape and associated parameter values; sampling each MRI scan in the training data set using the sampling shape and associated parameter values to generate a set of sparse samples; training a neural network using the sparse samples and assigning an accuracy to a resulting trained neural network; and adjusting the associated parameter values, and repeating the sampling and training until optimized parameter values are established.

Abstract: An image processing apparatus includes: an acquisition unit that acquires a radiographic image of a breast and information indicating a thickness of the breast in capture of the radiographic image; and a derivation unit that derives a percentage of mammary glands of a breast image in the radiographic image acquired by the acquisition unit using different methods in a case in which the thickness of the breast is equal to or greater than a predetermined thickness and a case in which the thickness of the breast is less than the predetermined thickness.

Abstract: The present invention relates to a method for characterizing perfusion abnormalities in tissue by means of fractal analysis (FA) of at least one part of an interface region between adequately and abnormally perfused tissue comprising the steps of providing an imaging dataset of perfusion imaging; wherein said imaging dataset visualizes the at least one part of the interface region; optional pre-processing of said imaging dataset; applying fractal analysis to the imaging dataset; wherein said fractal analysis provides at least one fractal parameter, preferably fractal dimension (FD), of the at least one part of the interface region.

Abstract: Methods and systems for using a position of a mobile device with an integrated display as an input to a video game or other presentation are presented. Embodiments include rendering an avatar on a mobile device such that it appears to overlay a competing user in the real world. Using the mobile device's position, view direction, and the other user's mobile device position, an avatar (or vehicle, etc.) is depicted at an apparently inertially stabilized location of the other user's mobile device or body. Some embodiments may estimate the other user's head and body positions and angles and reflect them in the avatar's gestures.

Abstract: The method of assisting the production of an implantable unfurlable made to measure device comprises: three-dimensional reconstruction of a complex surface of the cavity in which the device will be implanted; Production of a first finite element mesh of this complex surface; Choosing of generic components of the device; Production of a second finite element mesh of these assembled generic components; Determination of the morphosis parameters for morphosing from the first mesh to a mesh of a set of simple linked volumes which is representative of the part of the cavity, and then deformation of the first mesh by this morphosis; Simulation of a deformation of the second mesh, by inverse morphosis dependent on the determined parameters, to the complex surface, simulating unfurling of the device; Determination of dimensioning of points of interest by projection onto the second deformed mesh; and Generation of a production blueprint plan of the device.

Abstract: A web scaping system configured with artificial intelligence and image object detection. The system processes a web page with a neural network to perform object detection to obtain structured data, including text, image and other kinds of data, from web pages. The neural network allows the system to efficiently process visual information (including screenshots), text content and HTML structure to achieve good quality and decrease extraction time.

Abstract: Digital media assets depicting or otherwise representing portions of a property are captured via a media capture device, such as an unmanned vehicle, at various locations about a property. A positioning receiver tracks the location of the media capture device when each digital media asset is captured. A computing device associated with either the media capture device itself or a network-connected server automatically generates location-based categories—such as “front side” or “rear side” or “living room”—automatically based on the plurality of locations so that each location-based category is associated with multiple digital media assets and their corresponding locations.

Abstract: A method and system, the method including receive image data representations of a set of images of a physical asset; receive a data model of at least one asset, the data model of each of the at least one assets including a semantic description of the respective modeled asset and at least one operation associated with the respective modeled asset; determine a match between the received image data and the data model of one of the at least one assets based on a correspondence therebetween; generate, for the data model determined to be a match with the received image data, an operation plan based on the at least one operation included in matched data model; execute, in response to the generation of the operation plan, the generated operation plan by the physical asset.

Abstract: An information processing apparatus comprising: at least one processor programmed to cause the apparatus to: hold label information regarding presence of a target object, the label information being set for the target object in an image; obtain a reliability of the label information; cause a display apparatus to display the label information and an image corresponding to the label information in the image, based on the reliability; accept an operation made by a user; and modify the label information based on the operation.

Abstract: Example image processing methods, apparatus/systems and articles of manufacture are disclosed herein. An example apparatus includes an image recognition application to identify matches between stored patterns and objects detected in a shelf image, where the shelf image has a shelf image scale estimate. The example apparatus further includes a scale corrector to calculate deviation values between sizes of (A) a first set of the objects detected in the shelf image and (B) a first set of the stored patterns matched with the first set of the objects and reduce an error of the shelf image scale estimate by calculating a scale correction value for the shelf image scale estimate based on the deviation values.

Abstract: Provided are a tomography imaging apparatus and a method of reconstructing a tomography image which may more accurately measure a motion of an object to be tomography-imaged. In detail, the tomography imaging apparatus and the method of reconstructing a tomography image may obtain information indicating a motion of a moving object according to a time, may perform motion correction based on the obtained motion information, and may reconstruct a target image with reduced motion artifacts.

Abstract: A method and apparatus for determining a building/urban profile image location includes extracting a building/urban profile from an obtained image and comparing the image to a database of building/urban profiles. The database may be created by obtaining point cloud data sets scanned building/urban profiles, converting the obtained point cloud data sets to a corresponding 3D surface model, and creating the database of stored building/urban profiles viewed from multiple locations within each of the 3D surface models. By comparing the extracted building/urban profile image with the stored building/urban profiles contained within the database and finding a match the location from which the extracted building/urban profile image was taken can be determined.

Abstract: Missing image content is generated using a neural network. In an embodiment, a high resolution image and associated high resolution semantic label map are generated from a low resolution image and associated low resolution semantic label map. The input image/map pair (low resolution image and associated low resolution semantic label map) lacks detail and is therefore missing content. Rather than simply enhancing the input image/map pair, data missing in the input image/map pair is improvised or hallucinated by a neural network, creating plausible content while maintaining spatio-temporal consistency. Missing content is hallucinated to generate a detailed zoomed in portion of an image. Missing content is hallucinated to generate different variations of an image, such as different seasons or weather conditions for a driving video.