Abstract: A method for increasing Signal-to-Noise-Ratio (SNR) of defect detection in inspection of wafers or masks, the method including receiving a current image, receiving a reference image, receiving an indication for existence of a defect in the current image, producing a difference image between the current image and the reference image, performing singular value decomposition (SVD) on the difference image, removing one or more lower-valued singular values from a diagonal middle matrix produced by the SVD, thereby producing a reduced middle matrix, and producing an improved-SNR difference image by reconstructing the difference image using the reduced middle matrix. Related apparatus and methods are also described.

Abstract: The present invention refers to a computational script that aims to extract contour contrasts in images, to assist in the method for determining image facies The invention proposes a tool to highlight the heterogeneity of rocks for the identification of typical textural and structural patterns, being related to sedimentary facies. Use the “Canny Edge Detection” algorithm and parameterizations in a computational language environment in Python, to extract the contour contrasts observed in profiles of the images captured from the rocks. Other results achieved by the invention correspond to the removal of artifacts, images overlapping and edge contrasts quantification. These results were incorporated into a method for determining image facies. In addition, the use of the products generated in electrofacies, productivity and correlation prediction models between wells is promising. So the developed script provides important information for the oil industry.

Abstract: A data processing apparatus includes receiving circuitry to receive a plurality of images of an environment captured from respective different viewpoints, detection circuitry to detect a plurality of feature points in the plurality of captured images and to associate image information with each detected feature point indicative of an image property for a detected feature point, where each detected feature point represents a candidate landmark point for mapping the environment, selection circuitry to select one or more of the plurality of candidate landmark points, the one or more selected landmark points corresponding to a subset of the plurality of candidate landmark points, and mapping circuitry to generate, for the environment, a map including one or more of the selected landmark points, where each landmark point included in the map is defined by a three dimensional position and the associated image information for that landmark point.

Abstract: Provided are an apparatus and method for controlling a feed supply amount based on feed intake intention of livestock. The apparatus for controlling a feed supply amount based on feed intake intention of livestock includes a feed intake intention quantification part which perceives feed intake intention of livestock by using image information obtained by photographing a certain region within a livestock farm and quantifies the feed intake intention of livestock as a feed intake intention value, and a feed intake intention-based feed supply amount control part generating a command for controlling a feed supply amount in consideration of the feed intake intention value.

Abstract: A system for an automated processing of vision-based data for an automated door controller, including a processor of an automated door control server node configured to host a machine learning (ML) module and connected to at least one vision data capture entity and to at least one target controller of the automated door over a wireless network connection and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: acquire vision data from the at least one vision data capture entity reflecting a subject in a vicinity of the automated door, the vision data comprising a signal; normalize the signal for depth consistency; extract a set of classifying features reflecting movements of the subject relative to the automated door from the normalized signal; generate a classifier based on the set of classifying features; provide the classifier to the ML module configured to generate a predictive model based on a neural network for producing at least one dec

Abstract: Systems and methods for constructing high resolution panoramic imagery for feature identification on robotic devices are disclosed herein. According to at least one non-limiting exemplary embodiment, a robot collects a plurality of images of an environment, these images include large overlap in their visual scenes. Using additional image data from the overlapping images, resolution of labels, price tags, and other inventory tags may be enhanced when constructing panoramic imagery to improve feature identification.

Abstract: To enable high-speed autonomous flight of a flight object. A three-dimensional real-time observation result is generated on the basis of self-position estimation information and three-dimensional distance measurement information. A prior map corresponding to a three-dimensional real-time observation result is acquired. The three-dimensional real-time observation result and the prior map are aligned. After the alignment, the three-dimensional real-time observation result is expanded on the basis of the prior map. A flight route is set on the basis of the three-dimensional real-time observation result having been expanded. In the flight object such as a drone, a somewhat long flight route can be accurately calculated at a time in a global behavior plan, which enables high-speed autonomous flight of the flight object.

Abstract: In a case where the detection target is detected, an actual position display control process of displaying a detected position display circle on a display in an actual position display mode (single line) is performed. In a case where the detection target is not detected, an estimated position display control process of displaying an estimated position display circle on the display in an estimated position display mode (double line) different from the actual position display mode is performed.

Abstract: A system and method for dense depth map determination from image data, including: predicting a standard disparity map for the image using a standard disparity model based on the image; and converting the standard disparity map to a depth map using a focal length in pixels associated with the image.

Abstract: There is provided a method for training a ground truth generator machine learning model, comprising: creating a ground truth multi-record training dataset wherein a record comprises: a first image of a sample of tissue of a subject depicting a first group of biological objects, a second image of the sample depicting a second group of biological objects presenting at least one biomarker, and ground truth labels indicating a respective biological object category of a plurality of biological object categories for biological object members of the first group and the second group; and training the ground truth generator machine learning model on the ground truth multi-record training dataset for automatically generating ground truth labels selected from the plurality of biological object categories for biological objects depicted in an input set of images of a first type corresponding to the first image and a second type corresponding to the second image.

Abstract: A method of object detection in paired imaging includes detecting areas of interest for each image of a set of multi-view images, each detected area of interest having a corresponding initial probability of being an area of interest; determining a matching probability for each detected area of interest across the set of multi-view images such that detected areas of interest from one image of the set of multi-view images are assigned matching probabilities with respect to detected areas of interest of other images of the set of multi-view images; generating a modified probability for each detected area of interest according to one or more object-specific weighting factors and one or more of the matching probabilities for that detected area of interest; adjusting the initial probability of each detected area of interest using the modified probability to generate a refined probability for each detected area of interest; and identifying the detected areas of interest in each image that have refined probabilities

Abstract: A method for three-dimensionally modeling an eyeball and optical nerves using the merging of MRI images and OCT images, comprises: (a) a step for three-dimensionally modeling an eyeball model on the basis of the shapes of an eyeballs in a first MRI head image and a second MRI head image; (b) a step for three-dimensionally modeling an ASCO model in a corrected OCT eyeball cross-sectional image; (c) a step for three-dimensionally modeling the lamina cribrosa in the corrected OCT eyeball image; and (d) a step for generating an optic nerve model by three-dimensionally modeling an optic tract connected to the three-dimensionally modeled eyeball model.

Abstract: The present disclosure relates to a meter recognition method, which includes: determining embedded features of pixels in a target image of a meter, and encoding position information of the pixels to obtain encoded position features; inputting superimposed features obtained by superimposing the encoded position features and the embedded features into an encoder of a target model; wherein an input of the target model includes the labels, and an output of the target model includes coordinates of key points in a sample image of the meter. According to the present disclosure, the image of the meter can be processed by the trained target model, the coordinates of key points in the target image of the meter are outputted. It can reduce manual operations and improve efficiency, and on the other hand, it can avoid possible misoperations during manual operations, which is beneficial for improving accuracy.

Abstract: Systems, methods, and computer program products are provided for removing noise and/or artifacts from an image. The method includes training a generative adversarial network (GAN) based on a plurality of images, the plurality of images comprising at least one undesired element comprising at least one of the following: noise, speckle patterns, artifacts, or any combination thereof, and generating a modified image based on processing an image of an eye or other object with the GAN to remove the at least one undesired element from the image that is above an outer surface of the eye or other object.

Abstract: A system and method are provided for denoising images. A standard image module is configured to generate a standard anatomy feature and a standard noise feature from a standard image and reconstruct the standard image from the standard anatomy feature and the standard noise feature. A reduced quality image module is configured to generate a reduced quality anatomy feature and a reduced quality noise feature from a reduced quality image, and reconstruct the reduced quality image from the reduced quality anatomy feature and the reduced quality noise feature. A loss calculation module is provided for calculating loss metrics at least partially based on a comparison between 1) the reconstructed standard image and the standard image, and 2) the reconstructed reduced quality image and the reduced quality image. Upon providing the standard image module with the reduced quality anatomy feature, the standard image module outputs a reconstructed standard transfer image.

Abstract: This paper discloses a careless driving determination apparatus. The careless driving determination apparatus captures a plurality of face images of a driver of a vehicle in a predetermined period using a driver monitor camera. Then, it determines whether each of the plurality of face images shows first status in which the driver wears a wearing object or second status in which the driver does not wear the wearing object, the wearing object covering a part of a face of the driver. Then, it calculates a distribution range of angles of face directions or angles of gaze directions of the driver. Then, it sets a threshold range based on ratio of face images that show the first status and ratio of face images that show the second status. Then, it determines that the driver is in a careless driving state when the distribution range is included in the threshold range.

Abstract: An embodiment of the present invention provides a learning method, a learning apparatus, and a learning program for decomposing a two-dimensional X-ray image into a variety of regions, and an image processing method, an image processing apparatus, and an image processing program using a result of learning. A learning method according to an aspect of the present invention includes generating a masked CT image from a three-dimensional CT image, and generating a third pseudo X-ray image from the masked CT image. Then, a second pseudo X-ray image generated by projecting an original CT image is compared with the third pseudo X-ray image as a reference, and a parameter for use in generating the second pseudo X-ray image is updated based on a comparison result. A processor repeats the processing of each step until a predetermined condition is satisfied.

Abstract: The present disclosure achieves accurate tracking of sunlit orbital objects, including small, dim orbital debris, using a ground-based telescope and detector which tracks the orbital object. The angular position of the orbital object relative to background celestial objects is accurately determined over a trajectory, allowing accurate determination of the orbit parameters.

Abstract: In a method for enhancing accuracy and efficiency in automated visual inspection of vessels, a vessel containing a sample is oriented such that a line scan camera has a profile view of an edge of a stopper of the vessel. A plurality of images of the edge of the stopper is captured by the first line scan camera while spinning the vessel, where each image of the plurality of images corresponds to a different rotational position of the vessel. A two-dimensional image of the edge of the stopper is generated based on at least the plurality of images, and pixels of the two-dimensional image are processed, by one or more processors executing an inference model that includes a trained neural network, to generate output data indicative of a likelihood that the sample is defective.

Abstract: An output device including: a memory; and a processor coupled to the memory, the processor configured to: acquire a satellite image in which a target region is photographed and event information relating to events that have occurred in the target region; and output, from among roads in the target region, a road for which a safety degree calculated based on the satellite image and the event information is less than a threshold value.