Abstract: An image inspection device which enables the user to know the cause of an abnormality in a read image. The image inspection device includes: an image reader outputting a read image generated by reading an image formed on a sheet of paper by an image forming device; an image inspection section inspecting the read image and outputting an inspection result which takes the read image determined not to have an abnormality as a normal image and the read image determined to have the abnormality as an abnormal image; an inspection result report generator generating an inspection result report according to the read image and the inspection result; an inspection result report output section outputting the inspection result report; and a controller performing control to cause the inspection result report output section to output the normal image and the abnormal image in a comparable manner.

Abstract: Techniques described herein pertain to automated systems and methods for analyzing, storing, and/or retrieving information associated with biological objects including lymphocytes. In some embodiments, a shape metric is derived for each detected and segmented lymphocyte and the shape metric is stored along with other relevant data.

Abstract: A printing apparatus includes a reception unit configured to receive a print job, and an execution unit configured to execute printing of the print job received by the reception unit. The execution unit has a function of, in a case where a setting time or more elapses with a particular cause preventing the printing of the print job not being removed, canceling the printing of the print job. The execution unit has a function of canceling printing of a new print job received by the reception unit in a state where the setting time or more elapses with the particular cause not being removed.

Abstract: The objective of the present invention is to provide an image classification device and a method therefor with which suitable teaching data can be created. An image classification device that carries out image classification using images which are in a class to be classified and include teaching information, and images which are in a class not to be classified and to which teaching information has not been assigned, said image classification device being characterized by being provided with: an image group input unit for receiving inputs of an image group belonging to a class to be classified and an image group belonging to a class not to be classified; and a subclassification unit for extracting a feature amount for each image in an image group, clustering the feature amounts of the images in the image group belonging to a class not to be classified, and thereby dividing the images into sub-classes.

Abstract: Systems and techniques are provided for unsupervised scene-decompositional normalizing flows. An example process can include obtaining a scene-decompositional model having a normalizing flow neural network architecture. The process can include determining, based on processing data depicting multiple targets in a scene using the scene-decompositional model, a distribution of scene data as a mixture of flows from one or more background components and one or more foreground components. The process can further include identifying, based on processing the distribution of scene data using the scene-decompositional model, a target associated with the one or more foreground components and included in the data depicting the multiple targets in the scene.

Abstract: An image forming apparatus includes an image forming unit configured to perform image formation on a sheet, a casing configured to house the image forming unit, an operation unit configured to receive an operation performed by a user, an electric wire extending from the casing to be connected to the operation unit and configured to transmit an electrical signal, a reinforcing member provided separate from and independent of the electric wire, the reinforcing member interconnecting the casing and the operation unit, and a covering configured to enclose therein the electric wire and the reinforcing member, wherein the reinforcing member is fixed to the casing and the operation unit in such a manner that a distance between a portion fixed to the casing and a portion fixed to the operation unit in the reinforcing member is shorter than a total length of the electric wire.

Abstract: One embodiment provides a method, the method including: obtaining, using at least one sensor of an information handling device facilitating a video conference, at least one image of a portion of a user of the information handling device participating in the video conference, wherein at least one participant in the video conference is located remotely with respect to the user; identifying, using an image diagnosis system, a condition of the portion of the user by analyzing the at least one image of the portion of the user; and transmitting, using the image diagnosis system, the condition to the at least one participant. Other aspects are claimed and described.

Abstract: A method and system of recognizing and processing object edges and a computer-readable storage medium are provided. The method includes: obtaining an input image, where the input image includes an object with edges, and the edges of the object include a plurality of object vertices; recognizing, through an object vertex recognition model, the input image and obtaining a relative position of each object vertex and a corresponding image vertex thereof; determining an actual position of each object vertex in the input image according to the relative position of each object vertex and the corresponding image vertex thereof; and sequentially connecting adjacent object vertices to form edge lines to obtain the edges of the object with edges in the input image according to the actual position of each object vertex in the input image.

Abstract: An implement management system detects implement wear and monitors implement states to modify operating modes of a vehicle. The system can determine implement wear using the pull of the implement on the vehicle, the force and angle of which is represented by an orientation vector. The system may measure a current orientation vector and determine an expected orientation vector using sensors and a model (e.g., a machine learned model). Additionally, the implement management system can determine an implement state based on images of the soil and the implement captured by a camera onboard the vehicle during operation. The system may apply different models to the images to determine a likely state of the implement. The difference between the expected and current orientation vectors or the determined implement state may be used to determine whether and how the vehicle's operating mode should be modified.

Abstract: The techniques for dual-level semantic segmentation are provided. Data may be input to a first segmentation network. The input data comprises an image and label information associated with the image. The image may be captured at nighttime and may comprise a plurality of regions. At least one region among the plurality of regions may be determined based at least in part on output of the first segmentation network. The at least one region of the image may be cropped. The cropped at least one region may be input to a second segmentation network. A final output may be produced based on the output of the first segmentation network and output of the second segmentation network.

Abstract: An object tracking apparatus (1) includes: a first generation unit (221-224) for generating, based on a first position information (PIt-?) related to a position of an object (Ot-?) in a first image (IMt-?) captured at a first time (t-?) and a second position information (PIt) related to a position of an object (Ot) in a second image (IMt) captured at a second time (t), first and second feature vectors (CVt-?, CVt); and a second generation unit (225) for generating, as a correspondence information (AM) indicating a correspondence relationship between the object in the first image and the object in the second image, an information that is obtained by a calculation processing using the first and the second feature vectors.

Abstract: The invention is an image taking method in which images are taken with a microscope in an analyzing space at focal plane positions shifted with an equal step size, and an image is selected from the taken images for further image processing; the images are taken of a sediment of a liquid; the method includes: taking, in a first spatial region of the analyzing space, a first depth image sequence, and selecting from the first depth image sequence the image with the best contrast for further image processing, and taking, in a second spatial region of the analyzing space, a second depth image sequence with fewer images by taking into account the previous step, and selecting from the second depth image sequence the image with the best contrast for further image processing. The invention further includes an image analysis neural network for use with the above method.

Abstract: Techniques for optically detecting a subject chemical species within an atmospheric environment are disclosed. Image data is obtained representing multispectral imagery of a geographic region captured through the atmospheric environment. The image data includes an array of band-specific intensity values for each of a plurality of spectral bands, including a sample spectral band having increased sensitivity to the subject chemical species as compared to a plurality of reference spectral bands. A background reflectance map is generated that includes an array of inter-band intensity values in which each inter-band intensity value represents a filtered combination of band-specific intensity values of albedo-normalized arrays for a grouped subset of the plurality of reference spectral bands. The albedo-normalized array of band-specific intensity values for the sample spectral band is compared to the background reflectance map to obtain an index array of intensity variance values for the subject chemical species.

Abstract: Methods and apparatus for systems using a scene codec are described, where systems are either providers or consumers of multi-way, just-in-time, only-as-needed scene data including subscenes and subscene increments. An example system using a scene codec includes a plenoptic scene database containing one or more digital models of scenes, where representations and organization of representations are distributable across multiple systems such that collectively the multiplicity of systems can represent scenes of almost unlimited detail. The system may further include highly efficient means for the processing of these representation and organizations of representation providing the just-in-time, only-as-needed subscenes and scene increments necessary for ensuring a maximally continuous user experience enabled by a minimal amount of newly provided scene information, where the highly efficient means include a spatial processing unit.

Abstract: Systems, apparatus, and methods for occupancy tracking using augmented reality are disclosed herein. An example apparatus includes memory; instructions; and processor circuitry to execute the instructions to detect a first face in image data, the image data generated by image sensors in an environment and including at least a portion of the environment, the first face corresponding to a subject in the environment; define a first facial unit in the image data based on facial features associated with the first face; associate a first virtual object with the first facial unit in the image data; and determine an occupancy metric for the at least the portion of the environment based on the first virtual object and one or more other virtual objects associated with facial units defined in the image data.

Abstract: A display device for performing image processing by using a neural network including a plurality of layers, may obtain a plurality of pieces of model information respectively corresponding to pixels included in a first image based on object features respectively corresponding to the pixels; identify the plurality of pieces of model information respectively corresponding to the plurality of layers and the pixels input to the neural network based on information about a time point at which each of the pixels is processed in the neural network; update parameters of the plurality of layers, based on the plurality of pieces of model information; and obtain a second image by processing the first image via the plurality of layers to which the updated parameters are applied; and display the second image.

Abstract: A camera system for surgical navigation systems including a plurality of cameras mounted in a room. At least three cameras are mounted in the room which are operated in at least two different modes. In the first mode at least a subset of the cameras is operated to determine the position of markers and in a second mode at least a subset of the cameras is operated to determine the position of surfaces of the room.

Abstract: Example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, techniques to process pixel values sampled from a multi color channel imaging device. In particular, methods and/or techniques to process pixel samples for interpolating pixel values for one or more color channels.

Abstract: Systems and methods are provided for performing operations including: accessing a current structural estimate of a region of interest; generating a first simulated X-ray measurement based on the current structural estimate of the region of interest; receiving a first real X-ray measurement; and generating an update to the current structural estimate of the region of interest as a function of the first simulated X-ray measurement and the first real X-ray measurement, the update being generated invariant on the current structural estimate.

Abstract: 3D MRI images of the brain may be created and acquired. After administration of contrast, brain lesions and other abnormalities may be identified and isolated from the 3D MRI images, with each lesion serving as a region of interest (ROI). 3D region of contrast enhancement images may be created from segmented 3D MRI images and different regions of contrast enhancement of the brain lesion may be depicted. Saved regions of contrast enhancement may be converted into stereolithography format, maximum intensity projection (MIP) images, and/or orthographic projection images. Data corresponding to these resulting 3D region of contrast enhancement images may be used to create 3D printed models of the isolated region of contrast enhancement. Analysis of the 3D brain region of contrast enhancement images and the 3D printed region of contrast enhancement models may enable a more efficient and accurate way of determining brain lesion risk factors and effective treatment regimens.