Abstract: A support program is executable by a computer of an information processing device and supports a printer connected to the information processing device. The support program causes the computer to execute, determination processing of receiving print data corresponding to images having a plurality of pages from a general-purpose print program of an operating system and, based on the received print data, determining an arrangement order of the images according to the number of pages for one volume in a booklet printing, and composite image output control processing of transmitting the composite print data, which is made by rasterizing the composite image in which the images corresponding to the two target pages are arranged so as to fit on one surface of each sheet based on the arrangement order determined in the determination processing, from the information processing device to the printer.

Abstract: An image forming apparatus communicates with another device and includes a processor that controls the communication. A control unit controls the apparatus to operate in one of at least a first power saving state, a second power saving state, and a normal state. In the first power saving state, the apparatus is controlled so that an image forming unit, an image reading unit, and the control unit are not activated, and a communication device is activated. In the second power saving state, the apparatus is controlled so that at least one of the image forming unit and the image reading unit are not activated, and the communication device and the control unit are activated. In the normal state, the apparatus is controlled so that at least the image forming unit, the image reading unit, the communication device, and the control unit are activated.

Abstract: A image processing system which make it possible to reduce user time and effort in checking OCR error image data. The image processing system performs OCR processing on image data generated by an image forming apparatus in response to selection of an object by a user and stores the image data in a folder having a folder name formed by using a character string obtained by the OCR processing. The system includes a storage control unit configured to store the image data, in a case where the character string obtained by performing the OCR processing on the generated image data does not satisfy a predetermined condition, in a folder associated with the object.

Abstract: An input device that is mountable on an image forming apparatus includes a plurality of numerical keys arranged as hardware keys, a connector provided in a casing of the input device and configured to electrically connect the image forming apparatus and the input device, and a USB port provided in the casing and configured to USB-connect external equipment, which is different from the image forming apparatus, to the input device. As viewed in an up-down direction that the numerical keys are pressed, the USB port is provided on a front side surface of the casing.

Abstract: Herein are feature extraction mechanisms that receive parsed log messages as inputs and transform them into numerical feature vectors for machine learning models (MLMs). In an embodiment, a computer extracts fields from a log message. Each field specifies a name, a text value, and a type. For each field, a field transformer for the field is dynamically selected based the field's name and/or the field's type. The field transformer converts the field's text value into a value of the field's type. A feature encoder for the value of the field's type is dynamically selected based on the field's type and/or a range of the field's values that occur in a training corpus of an MLM. From the feature encoder, an encoding of the value of the field's typed is stored into a feature vector. Based on the MLM and the feature vector, the log message is detected as anomalous.

Abstract: A transformer based vision-linguistic (VL) model and training technique uses a number of different image patches covering the same portion of an image, along with a text description of the image to train the model. The model and pre-training techniques may be used in domain specific training of the model. The model can be used for fine-grained image-text tasks in the fashion domain.

Abstract: An electronic apparatus is provided. The electronic apparatus includes a user interface, a camera, a memory configured to store a first artificial intelligence model trained to obtain information on an emotion based on an input image, and a processor, connected to the user interface, the camera, and the memory, configured to control the electronic apparatus. The processor is configured to, based on text being input through the user interface, identify whether the text includes first information on a user's emotion, based on the text including the first information, obtain second information for the emotion by inputting the image obtained through the camera to the first artificial intelligence model, and identify a type of the user's emotion based on the first information obtained from the text and the second information obtained from the image.

Abstract: A method of feature extraction from an image can include receiving the image including pixels, generating confidence values corresponding to positions of the pixels in the image by an artificial intelligence (AI) based feature extractor, selecting a first position among the positions of the pixels in the image, a first confidence value among the generated confidence values at the first position being higher than a first threshold, and generating a final set of keypoint-descriptor pairs based on the confidence values corresponding to positions of the pixels in the image. The final set of keypoint-descriptor pairs includes at least two keypoint-descriptor pairs corresponding to the first position among the positions of the pixels in the image.

Abstract: An information processing device includes a processor holding restoration information that associates (i) defects predicted to occur in an inspection image read from a recording medium, (ii) a restoration operation for preventing each of the defects from occurring, and (iii) an executing device that executes the restoration operation, with one another. The processor extracts, from the restoration information, the restoration operation associated with one of the defects designated on a display screen displaying the inspection image read from the recording medium, and instructs the executing device to execute the extracted restoration operation.

Abstract: A method includes: generating a refine image having a maximized correct label score of inference from an incorrect image from which an incorrect label is inferred by a neural network; generating a third map by superimposing a first map and a second map, the first map indicating pixels to each of which a change is made in generating the refine image, of a plurality of pixels of the incorrect image, the second map indicating a degree of attention for each local region in the refine image, the each local region being a region that has drawn attention by the neural network; and specifying a set of pixels that cause incorrect inference in the incorrect image by calculating a pixel value of the third map for each set of pixels, wherein the map generating processing adjusts the second map based on appearance frequency of each degree of attention.

Abstract: An apparatus includes a setting unit and a control unit. The setting unit performs a first print setting indicating a poster printing function that divides a single piece of image data into a plurality of pieces of image data and generates print jobs, and a second print setting indicating a correction function for correcting calculated gray values when an image processing apparatus converts a plurality of pieces of color image data to grayscale, based on a number of colors acquired from each of the plurality of pieces of color image data. The control unit restricts the setting unit from performing the first print setting and the second print setting. In a state where one of the first print setting and the second print setting is performed by the setting unit, the control unit controls the setting unit not to perform the other print setting.

Abstract: Systems and methods for on-board selection of data logs for training a machine learning model are provided. The system includes an autonomous vehicle having a plurality of sensors and a processor. The processor receives a plurality of unlabeled images from the plurality of sensors, a machine learning model, and a loss function corresponding to the machine learning model. For each of the plurality of images, the processor then determines one or more predictions using the machine learning model, compute an importance function based on the loss function and the one or more predictions, and transmit that image to a remote server for updating the machine learning model when a value of the importance function is greater than a threshold.

Abstract: An information processing apparatus includes a processor configured to extract a description including a phrase indicating a relation with a second document element from a first document element, and generate relation information corresponding to information on the description extracted from the first document element, by an AI which has learned, in advance, by machine learning to generate the relation information indicating a relation between the first document element and the second document element from the information on the description.

Abstract: The system and method for super resolution processing at long standoff distances in real-time. The system collects a series of image frames and estimated the shift, rotation, and zoom parameters between each of the image frames. A matrix is generated and then an inversion is applied to the matrix to produce a super resolution image of an area of interest while mitigating the effect of any bad pixels on image quality. In some cases, the area of interest is user-defined and in some cases image chips are provided by tracking software. A fast steering mirror can be used to steer and/or dither the focal plane array.

Abstract: A computer, including a plurality of processing nodes arranged in two-dimensional arrays in respective front and rear layers. Each processing node has a set of activatable links. When activated, transmission of data items between the nodes connected via the activated link is enabled. When not activated, transmission of data items between the nodes is prevented. The set of activatable links including a respective link which connects the processing node to each adjacent node in the array, and to a facing processing node in the other layer. An allocation engine is configured to receive an allocation instruction and connected to the processing nodes to selectively activate the links in a configuration.

Abstract: An image processing apparatus that processes an image of a recognition target on a mounting surface captured by an image pickup apparatus, the image processing apparatus includes an extraction unit configured to extract an area from the image based on a first distance from the recognition target to the image pickup apparatus, a height of a designated recognition target, and a second distance from the image pickup apparatus to the mounting surface, and a recognition unit configured to perform recognition processing on the area.

Abstract: A tiered processing scheme for processing image data is provided. A method can include obtaining image data indicative of one or more court judgment(s) with a number of features. The method can include obtaining judgment information from the image data by applying a number of image processing techniques in accordance with a processing hierarchy tailored to the image data. The image data can be classified by a machine-learning model and the processing hierarchy can be determined based on the classification. The processing hierarchy balances the computing resources used by a respective technique with the accuracy afforded by the technique when applied to image data with a respective classification. A computing system can utilize the processing hierarchy to leverage different image processing techniques in a tiered processing scheme tailored to image data.

Abstract: Systems and methods for answering region specific questions are provided. A method includes obtaining a regional scene question including an attribute query and a spatial region of interest for a training scene depicting a surrounding environment of a vehicle. The method includes obtaining a universal embedding for the training scene and an attribute embedding for the attribute query of the scene question. The universal embedding can identify sensory data corresponding to the training scene that can be used to answer questions concerning a number of different attributes in the training scene. The attribute embedding can identify aspects of an attribute that can be used to answer questions specific to the attribute. The method includes determining an answer embedding based on the universal embedding and the attribute embedding and determining a regional scene answer to the regional scene question based on the spatial region of interest and the answer embedding.

Abstract: Techniques for a service provider network to provide users with software components that pre-process raw data stored in user computing networks to generate training data that is usable by artificial-intelligence (AI) services. The AI services may utilize models to provide various functionality to users, and the users may desire to train the models with data sets that are specific to their data sets. The service provider network can develop software components that are configured to process raw data into training data for various AI services. The software components can be provided to the user computing networks and executed locally, rather than the raw data having to being moved from the user computing network and to the service provider network. The training data can then be sent to the service provider network and used by the AI services to train ML models for use by the user.

Abstract: According to an aspect of some embodiments, an information processing apparatus is configured to perform: displaying an operation screen in a display, the operation screen generated by instructing a WebView to process the obtained web contents; if a predetermined instruction is given through the operation screen, calling the native library by using a script contained in the web contents, and instructing the called native library to generate image data corresponding to the file; and displaying the image data generated by the native library in the operation screen.