Abstract: Embodiments provide systems and methods for securely transferring large objects. A computer-implemented method, for example, includes determining whether digital content captured by a content capture device currently qualifies as a large file for transmission, based on a size attribute and a current transmission parameter associated with currently transmitting objects from a content capture system to an enterprise content management system. If the digital content qualifies as a large file, the digital content is encrypted and transmitted to a decentralized storage system for storage, and a content identifier that identifies the encrypted digital content stored in the decentralized storage system is transmitted to the enterprise content management system. Otherwise, the digital content is transmitted from the content capture system to the enterprise content management system.

Abstract: A reading device connected to an external device include a transport section configured to transport a document, a reading section configured to read the document transported by the transport section, a data generation section configured to generate image data of the document read by the reading section; a transfer section configured to transfer the image data to the external device, a notification section configured to notify information to a user, and a control section, wherein the control section is configured to control a transport speed of the document by the transport section based on a transfer speed of the image data by the transfer section and, when the transport speed is changed, to cause the notification section to notify using a change notification A1 indicating a change in the transport speed.

Abstract: A printed-matter inspection system includes a processor for evaluating quality of printed matter, and a display apparatus. The processor is configured, by reading a program for execution, to: for each of multiple pages in a job, if the page is an inspection target, compare, for inspection, a scanned image with a reference image, the scanned image being obtained through scanning of printed matter in the page, the reference image being generated by using rasterized data for the page; and, in display of the result of the inspection on the display apparatus, display the scanned image for the page that is an inspection target, and display, for a page that is not an inspection target, a dummy page and information indicating that the page is not an inspection target, the dummy page being a substitute of the scanned image.

Abstract: A pre-training method for a Vision and Scene Text Aggregation model includes: acquiring a sample image-text pair; extracting a sample scene text from a sample image; inputting a sample text into a text encoding network to obtain a sample text feature; inputting the sample image and an initial sample aggregation feature into a visual encoding subnetwork and inputting the initial sample aggregation feature and the sample scene text into a scene encoding subnetwork to obtain a global image feature of the sample image and a learned sample aggregation feature; and pre-training the Vision and Scene Text Aggregation model according to the sample text feature, the global image feature of the sample image, and the learned sample aggregation feature.

Abstract: A computer is caused to perform processing of: acquiring a plurality of medical images generated based on signals detected by a catheter inserted into a lumen organ while the catheter is moving a sensor along a longitudinal direction of the lumen organ, the lumen organ including a main trunk, a side branch branched from the main trunk, and a bifurcated portion of the main trunk and the side branch; and recognizing a main trunk cross-section, a side branch cross-section, and a bifurcated portion cross-section by inputting the acquired medical images into a learning model configured to recognize the main trunk cross-section, the side branch cross-section, and the bifurcated portion cross-section.

Abstract: Introduced here are computer programs that are able to generate computer vision data through local analysis of image data (also referred to as “raw data” or “input data”). The image data may be representative of one or more digital images that are generated by an image sensor. Also introduced here are apparatuses for generating and handling the image data and computer vision data.

Abstract: An image processing apparatus includes an input unit configured to input image data; a generation unit configured to generate image data having undergone color gamut conversion from the image data input by the input unit using a conversion unit configured to convert a color gamut of the image data input by the input unit into a color gamut of a device configured to output the image data; a correction unit configured to correct the conversion unit based on a result of the color gamut conversion; and a control unit configured to control execution of the correction by the correction unit for an object included in the image data input by the input unit.

Abstract: An image processing device 10 includes an image interface 18, a memory 19, and a controller 20. The image interface 18 acquires a captured image. The positions of specific feature points in a world coordinate system and reference positions of the specific feature points are stored in the memory 19. The controller 20 detects the specific feature points in the captured image. In a case where discrepancy between the position in the captured image and the reference position is found with regard to a predetermined percentage or more of the specific feature points, the controller 20 recalculates a calibration parameter.

Abstract: An image analyzer including: an area setting unit configured to extract a scratch area that is an area having no cells from a reference image selected from a plurality of images acquired by imaging cells in a time series and set a reference region corresponding to the scratch area in the plurality of images; a calculation unit configured to calculate an area of a cell region within the reference region and/or the ratio of an area of the cell region to the reference region from the plurality of images; and a control unit configured to cause a display device to display a change in a time series of the calculated area of the cell region and/or the ratio of the area of the cell region to the reference region.

Abstract: A display control device controls a display screen for displaying a preview of a print image to be printed on a recording medium by using an ink. The print image is printed using, as the ink, a structural color ink of which a color changes due to an optical phenomenon caused by a structure, and a color of the print image changes depending on an angle of visual recognition. The display control device includes: a processor. In a case where the print image is visually recognized at different angles, the processor is configured to display, on the display screen, a plurality of preview images corresponding to the angles by performing color conversion processing corresponding to the structural color ink.

Abstract: A recording apparatus includes: a recording unit configured to perform recording of an image on a recording medium by using recording material; and a controller configured to execute a recording control regarding the recording. The controller is configured to execute an adjustment processing for adjusting an amount of the recording material to be used in the recording, and the controller is configured to change a processing other than the adjustment processing in the recording control between a case that the adjustment processing is executed and a case that no adjustment processing is executed.

Abstract: A method comprising: receiving image data associated with a plurality of semen samples; at a training stage, training a machine learning model on a training set comprising: (i) said image data, and (ii) labels associated with a qualitative assessment of each of one or more individual spermatozoa in said semen samples; and applying said trained machine learning model to target image data associated with a target semen sample, to identify one or more spermatozoa in said target sample as candidates for an ART procedure.

Abstract: A method for detection and characterization of lesions includes acquiring a plurality of phase images of a multi-phase imaging exam, extracting a local context for each phase image of the plurality of phase images, encoding the local contexts to create phase specific feature maps, combining the phase-specific feature maps to create unified feature maps, and at least one of characterizing or detecting a lesion based on the unified feature maps.

Abstract: An example image forming device includes a wakeup source to detect an event for cancelling a power saving mode of the image forming device, a display, a processor, and a memory to store instructions executable by the processor. By executing the instructions, the processor is to display, through the display, a setting screen including a user interface to set an operation of the wakeup source, obtain information on a condition for cancelling the power saving mode based on setting information of the wakeup source received from the setting screen, and cancel the power saving mode in a case where a cancellation condition included in the information on the condition for cancelling the power saving mode is met in the power saving mode.

Abstract: The invention relates to a computer-implemented method for automatically detecting anatomical structures (3) in a medical image (1) of a subject, the method comprising applying an object detector function (4) to the medical image, wherein the object detector function performs the steps of: (A) applying a first neural network (40) to the medical image, wherein the first neural network is trained to detect a first plurality of classes of larger-sized anatomical structures (3a), thereby generating as output the coordinates of at least one first bounding box (51) and the confidence score of it containing a larger-sized anatomical structure; (B) cropping (42) the medical image to the first bounding box, thereby generating a cropped image (11) containing the image content within the first bounding box (51); and (C) applying a second neural network (44) to the cropped medical image, wherein the second neural network is trained to detect at least one second class of smaller-sized anatomical structures (3b), thereby g

Abstract: An image forming system includes an image forming apparatus and a management apparatus. The image forming apparatus includes a variable mechanism, a physical quantity detection unit that detects a change in physical quantity caused when a state of the variable mechanism changes, an abnormality detection unit that detects an abnormal condition, and a transmission unit that transmits detection results of the physical quantity detection unit and the abnormality detection unit to the management apparatus. The management apparatus includes a determination unit that determines a cause of the abnormal condition, and a notification unit that provides a notification that the abnormal condition is caused by a change in the state in accordance with a determination result. The determination unit determines that the abnormal condition is caused by a change in the state when the abnormal condition is detected after the change in physical quantity exceeds a threshold.

Abstract: An inspection apparatus that reads an image formed on a printed material to generate a reference image of an inspection target, and specifies each region including an object in the reference image, and displays the regions such that the regions are selectable. Also, the inspection apparatus batch-sets inspection conditions for a plurality of regions selected by the user via the displayed reference image. Further, the inspection apparatus disables batch setting of an inspection condition in a case where a plurality of regions selected by the user include different regions that include objects of different inspection types. On the other hand, in a case where a plurality of regions selected by the user do not include such different regions, the inspection apparatus enables batch setting of an inspection condition.

Abstract: An inspection system extracts feature points from a scan image and from a reference image, performs alignment of the scan image and the reference image based on the extracted feature points, inspects a printed material using the aligned scan and reference images, and performs processing in accordance with a method selected from among a plurality of methods including at least a first method and a second method in a case where the number of the feature points in the reference image is less than a predetermined number. The processing is performed such that, in the case where the number of the feature points in the reference image is less than the predetermined number, the alignment using at least the extracted feature points is performed when the first method is selected, and the inspection is then carried out, whereas the inspection is not carried out when the second method is selected.

Abstract: An apparatus may include a housing defining a first opening, a second opening, and a cavity connecting the first opening to the second opening, the cavity may receive a user's extremity through the first opening and to allow egress through the second opening. An apparatus may include a visualization module configured to superimpose visual media equivalent to a desired tattoo onto the user's extremity within the cavity. An apparatus may include a printer module disposed within the cavity to apply the desired tattoo, the printer module including one or more print heads for administering temporary tattoo ink to apply the temporary tattoo to the user's extremity. An apparatus may include a user interface terminal configured to allow a user to select the temporary tattoo from among a number of candidate temporary tattoos and to adjust one or more properties of the temporary tattoo prior to application of the temporary tattoo.

Abstract: A method, system and apparatus for rendering a gloss effect on a recording medium, can involve rendering a foreground pattern using a first ink composition comprising infrared absorbing colors, wherein said first ink is lightened with lightening parameters by the addition of paper white holes and rendering a background pattern using a second ink composition comprising a process or spot color, wherein said second ink is darkened with darkening parameters by the addition of infrared absorbing colors that have different amounts of infrared absorbing colors than that of the first ink composition. The lightening parameters and the darkening parameters are adjustable to ensure that the first and second inks appear approximately the same at printed sizes. Anisotropic properties can be introduced to the first and second inks, causing non-uniformity in their reflection of light in different directions when viewed under a light source, thereby creating a gloss effect renderable on a recording medium.