Abstract: An image processing method includes: extracting, based on pixel values of a plurality of pixels of an image obtained, a plurality of first current pixels having pixel values included in a first color range including a specific color range that defines a specific color, from the plurality of pixels; excluding, in second region different from a first region including a center region of the image, (i) a low saturation pixel from the plurality of first current pixels when the number of low saturation pixels is greater than or equal to a first threshold value, and (ii) a high saturation pixel, which has a pixel value included in a high saturation range, from the plurality of first current pixels when the number of high saturation pixels is greater than or equal to a second threshold value; and outputting a plurality of second current pixels obtained as a result of the excluding.

Abstract: A control method for a scanning system that reduces load on an information processing apparatus when transmitting scanned data to a cloud server requiring an access token is provided. The control method includes acquiring, by an information processing apparatus, an access token from an authorization server, transmitting, by the information processing apparatus, the access token and an address of a cloud server in a first transmission, receiving, by an image forming apparatus, the address and the access token transmitted in the first transmission, scanning, by the image forming apparatus, a document based on the reception of the address and the access token, and transmitting, by the image forming apparatus, the image data generated by scanning the document and the access token to the cloud server in a second transmission.

Abstract: The present application provides a model training, image processing method, device, storage medium, and program product relating to deep learning technology, which are able to screen auxiliary image data with image data for learning a target task, and further fuse the target image data and the auxiliary image data, so as to train a built and to-be-trained model with the fusion-processed fused image data. This implementation can increase the amount of data for training the model, and the data for training the model is determined is based on the target image data, which is suitable for learning the target task. Therefore, the solution provided by the present application can train an accurate target model even if the amount of target image data is not sufficient.

Abstract: An object of the present disclosure is to provide a mechanism capable of performing thickening processing of an object irrespective of the color of a line even in a case where the black over print is valid. One embodiment of the present invention is an image forming apparatus comprising a control unit configured to control whether or not to perform thickening processing to thicken an object in an upper layer and an object in a lower layer based on a raster operation code designating drawing processing in a case where the object in the upper layer and the object in the lower layer overlap, wherein the control unit: does not perform the thickening processing in a case where a value of the raster operation code is MERGEPEN and a color of the object in the upper layer is not a black color.

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: A metrology system includes one or more through-focus imaging metrology sub-systems communicatively coupled to a controller having one or more processors configured to receive a plurality of training images captured at one or more focal positions. The one or more processors may generate a machine learning classifier based on the plurality of training images. The one or more processors may receive one or more target feature selections for one or more target overlay measurements corresponding to one or more target features. The one or more processors may determine one or more target focal positions based on the one or more target feature selections using the machine learning classifier. The one or more processors may receive one or more target images captured at the one or more target focal positions, the target images including the one or more target features of the target specimen, and determine overlay based thereon.

Abstract: Systems, methods, and computer program products may be configured to generate a set of related document objects for a predictive entity and/or to generate an optimal document sequence for a set of related document objects. In one embodiment, for example, a set of related document objects for a predictive entity is generated by processing entity metadata features associated with the predictive entity using an entity-document correlation machine learning model, and an optimal document sequence is generated for the set of related document objects by processing the set of related document objects using a document sequence optimization machine learning model.

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: An information processing apparatus includes a processor configured to execute a rasterization process of forming image data recognizable by a printing apparatus on the basis of a print request and an inspection process of inspecting a print medium on the basis of inspection image data obtained by reading the print medium subjected to a printing process, and execute the inspection process with first inspection accuracy that is lower than highest inspection accuracy realizable by the processor in a case where the print request includes an instruction for plural-copy printing and does not include an instruction for variable printing.

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.

Abstract: A non-transitory computer-readable medium storing a support program readable by a computer of an information processing device, the support program corresponding to a printer connected to the information processing device and supporting a general-purpose print program pre-installed in an operating system of the information processing device, the support program, when executed by the computer, causes the computer to perform: based on a print instruction being output from an application program installed in the information processing device and transferred to the general-purpose print program to cause the printer to perform printing, receiving intermediate image data according to the print instruction from the operating system; generating rasterized raster data based on the received intermediate image data; compressing the generated raster data; and transmitting print data based on the compressed raster data to the printer.

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: Provided is an image processing apparatus that performs image processing on original image data, the apparatus including a communication unit that performs communication with a terminal, a storage that stores parameter information indicating a relationship between image processing-related information transmitted from the terminal and an image processing parameter, and a processor, in which the processor acquires the original image data, performs, in a case in which an image processing request including the image processing-related information is received from the terminal via the communication unit, the image processing on the original image data using the image processing parameter corresponding to the image processing-related information based on the parameter information, and transmits image data after the image processing to the terminal via the communication unit.

Abstract: Provided are aspects relating to methods and computing devices for allocating computing resources and selecting hyperparameter configurations during continuous retraining and operation of a machine learning model. In one example, a computing device configured to be located at a network edge between a local network and a cloud service includes a processor and a memory storing instructions executable by the processor to operate a machine learning model. During a retraining window, a selected portion of a video stream is selected for labeling. At least a portion of a labeled retraining data set is selected for profiling a superset of hyperparameter configurations. For each configuration of the superset of hyperparameter configurations, a profiling test is performed. The profiling test is terminated, and a change in inference accuracy that resulted from the profiling test is extrapolated. Based upon the extrapolated inference accuracies, a set of selected hyperparameter configurations is output.

Abstract: A system that includes artificial intelligence (AI) configured to identify text and images within an industrial reference. Example industrial references include electrical drawings and P&IDs. The system includes a method for training artificial intelligence model to recognize text characters and strings in addition to industrial images using a limited sample set. The use of a limited sample set improves computer performance by relying on a smaller dataset to train the model.

Abstract: Atomic position data may be obtained from x-ray diffraction data. The x-ray diffraction data for a sample may be squared and/or otherwise operated on to obtain input data for a neural network. The input data may be input to a trained convolutional neural network. The convolutional neural network may have been trained based on pairs of known atomic structures and corresponding neural network inputs. For the neural network input corresponding to the sample and input to the trained convolutional neural network, the convolutional neural network may obtain an atomic structure corresponding to the sample.

Abstract: A method for extracting a video clip includes obtaining a video and splitting the video into multiple clips. The multiple clips are input into a pre-trained scoring model, to obtain a score of each of the multiple clips. The scoring model is obtained by training based on data pairs including first clips and second clips, the data pairs including first clips and second clips are obtained based on labeled clips labeled with target attributes, and the target attributes include attributes that characterize clips as target clips or non-target clips. A target clip is extracted from the multiple clips based on the score of each of the multiple clips. An apparatus for extracting a video clip and a computer readable storage medium are also disclosed.

Abstract: Apparatuses, systems, and techniques to train a generative model based at least in part on a private dataset. In at least one embodiment, the generative model is trained based at least in part on a differentially private Sinkhorn algorithm, for example, using backpropagation with gradient descent to determine a gradient of a set of parameters of the generative models and modifying the set of parameters based at least in part on the gradient.

Abstract: A printing apparatus management server manages a plurality of printing apparatuses, obtains, in response to a request from a voice device management server, information of a predetermined printing apparatus registered, from the plurality of printing apparatuses, as a printing apparatus to be used in the printing apparatus management server, transmits, to the voice device management server, the obtained information of the predetermined printing apparatus, obtains remaining amount information transmitted from the predetermined printing apparatus, and transmits the obtained remaining amount information to the consumable item management server. Voice notification to a user is performed, via a voice device configured to communicate with the voice device management server, based on the obtained remaining amount information, and processing for placing an order for the consumable item is performed based on a voice instruction from the user accepted by the voice device.

Abstract: According to various embodiments, a system and method for processing an image of a biological specimen stained for a presence of at least one lymphocyte biomarker is disclosed. The system and method are configured to detect lymphocytes in the image and compute a foreground segmentation mask based on the lymphocytes detected within the image. Outlines of the detected lymphocytes are identified in the image by filtering the image with the computed foreground segmentation mask. A shape metric may be derived for each of the detected lymphocytes based on the identified lymphocytes outlines. The derived shape metric may be associated with location information for each of the detected lymphocytes and a value of each of the derived shape metric may be compared to a predetermined threshold value. A predictive cell motility label may be assigned to each of the detected lymphocytes based on the comparison.