Abstract: Apparatus, systems, and methods to generate an edge aware brush for navigation and segmentation of images via a user interface are disclosed. An example processor is to at least: construct a brush for segmentation of image data; provide an interactive representation of the brush with respect to the image data via a user interface, the interactive representation to be displayed and made available for interaction in each of a plurality of viewports provided for display of views of the image data in the user interface; enable update of the viewports based on manipulation of the representation; facilitate display of a preview of a segmentation of the image data corresponding to a location of the representation; and, when the segmentation is confirmed, facilitate generation of an output based on the segmentation.

Abstract: The present invention relates to an image encoding and decoding technique, and more particularly, to an image encoder and decoder using unidirectional prediction. The image encoder includes a dividing unit to divide a macro block into a plurality of sub-blocks, a unidirectional application determining unit to determine whether an identical prediction mode is applied to each of the plurality of sub-blocks, and a prediction mode determining unit to determine a prediction mode with respect to each of the plurality of sub-blocks based on a determined result of the unidirectional application determining unit.

Abstract: The present disclosure relates to an object selection system that automatically detects and selects objects in a digital image utilizing a large-scale object detector. For instance, in response to receiving a request to automatically select a query object with an unknown object class in a digital image, the object selection system can utilize a large-scale object detector to detect potential objects in the image, filter out one or more potential objects, and label the remaining potential objects in the image to detect the query object. In some implementations, the large-scale object detector utilizes a region proposal model, a concept mask model, and an auto tagging model to automatically detect objects in the digital image.

Abstract: An intra prediction method and a device using the intra prediction method are provided. The intra prediction method includes the steps of: deriving a current prediction mode as a prediction mode of a current block; constructing neighboring samples of the current block with available reference samples; filtering the available reference samples; and generating predicted samples of the current block on the basis of the filtered available reference samples. The filtering step includes performing the filtering using the available reference sample located in the prediction direction of the current prediction mode and a predetermined number of available reference samples neighboring to the prediction direction of the current prediction mode.

Abstract: The present system for modeling intelligent sensor selection and placement takes signal and sensor information and calculates a statistical inference. As signal data passes through a series of processors, it is transformed by functions to account for signal emission, sensor reception, environmental factors, and noise. This produces a simulation of what the emitted signal would appear to be at a given sensor. The system may be used to select the most effective sensors for a given area or to determine the best sensor coverage for a given area.

Abstract: The present invention relates to a technique for encoding and decoding video data, and more particularly, to a method for performing inter-prediction in an effective manner. The present invention combines an inter-prediction method using an AMVP mode and an inter-prediction method using a merge mode so as to propose a method for using the same candidate. The method for encoding video data proposed by the present invention comprises the following steps: receiving mode information on an inter-prediction method of a current block; determining, on the basis of the received mode information, whether the interprediction method to be applied to the current block is an AMVP mode or a merge mode; and selecting a candidate to derive motion information of the current block, wherein the candidate is selected in a left region, top region and corner region of the current block and in the same position block as the current block, and the AMVP mode and the merge mode are applied on the basis of the selected candidate.

Abstract: Examples of systems and method described herein provide for the processing of image codes (e.g., a binary embedding) at a memory die. Such images codes may generated by various endpoint computing devices, such as Internet of Things (IoT) computing devices, Such devices can generate a Hamming processing command, having an image code of the image, to compare that representation of the image to other images (e.g., in an image dataset) to identify a match or a set of neural network results. Advantageously, examples described herein may be used in neural networks to facilitate the processing of datasets, so as to increase the rate and amount of processing of such datasets. For example, comparisons of image codes can be performed on a memory die itself, like a memory die of a NAND memory device.

Abstract: A dependency indication is signaled within the beginning of a packet, that is, within the adjacent of a slice header to be parsed or a parameter set. This is achieved, for example, by including the dependency indication at the beginning of the slice header, preferably after a syntax element identifying the parameter set and before the slice address, by including the dependency indication before the slice address, by providing the dependency indication to a NALU header using a separate message, or by using a special NALU type for NALUs carrying dependent slices.

Abstract: Provided are an optical device which is capable of optically implementing an activation function of an artificial neural network and an optical neural network apparatus which includes the optical device. The optical device may include: a beam splitter splitting incident light into first light and second light; an image sensor disposed to sense the first light; an optical shutter configured to transmit or block the second light; and a controller controlling operations of the optical shutter, based on an intensity of the first light measured by the image sensor.

Abstract: Apparatus for binning an input value into an array of bins, each bin representing a range of input values and the bins collectively representing a histogram of input values, the apparatus comprising: an input for receiving the input value; a memory for storing the array; and a binning controller configured to: derive a plurality of bin values from the input value according to a binning distribution located about the input value, the binning distribution spanning a range of input values and each bin value having a respective input value dependent on the position of the bin value in the binning distribution; and allocate the plurality of bin values to a plurality of bins in the array, each bin value being allocated to a bin selected according to the respective input value of the bin value.

Abstract: An image encoder is provided including circuitry and a memory coupled to the circuitry. The circuitry, in operation, responds to a size of a block satisfying a size condition by generating a prediction image using a prediction mode selected from a plurality of prediction modes. The plurality of prediction modes include a first prediction mode in which a prediction process uses a motion vector and a reference block in a same picture as the block. The circuitry encodes the block using the prediction image.

Abstract: A method of mapping 3D point cloud data into 2D surfaces for further efficient temporal coding is described herein. Point cloud global tetris packing utilizes 3D surface patches to represent point clouds and performs temporally consistent global mapping of 3D patch surface data into 2D canvas images.

Abstract: A patient interface for supplying a flow of breathable gas to the airways of a patient may comprise a heat and moisture exchanger (HME). The HME may be positioned in a flow path of the flow of breathable gas. The HME may absorb heat and moisture from gas exhaled by the patient and the incoming flow of breathable gas to be supplied to the patient's airways may be heated and moisturized by the heat and moisture held in the HME.

Abstract: A control apparatus includes a detection unit configured to detect an object area in an image captured by an image capturing apparatus, a dividing unit configured to divide the image into a plurality of divided areas, a first calculation unit configured to calculate a luminance difference as a difference between a luminance value of the object area and a luminance value of each of the divided areas, a second calculation unit configured to calculate a first amount of change as a difference between luminance values of the object area before and after the image capturing apparatus executes exposure control and a second amount of change as a difference between luminance values of the divided area before and after the image capturing apparatus executes exposure control, and a determination unit configured to determine a photometric area.

Abstract: An image fusion system provides a predicted alignment between images of different modalities and synchronization of the alignment, once acquired. A spatial tracker detects and tracks a position and orientation of an imaging device within an environment. A predicted pose of an anatomical feature can be determined, based on previously acquired image data, with respect to a desired position and orientation of the imaging device. When the imaging device is moved into the desired position and orientation, a relationship is established between the pose of the anatomical feature in the image data and the pose of the anatomical feature imaged by the imaging device. Based on tracking information provided by the spatial tracker, the relationship is maintained even when the imaging device moves to various positions during a procedure.

Abstract: The present disclosure provides systems and methods for predicting a disease state of a subject using ultrasound imaging and ancillary information to the ultrasound imaging. At least two quantitative measurements of a subject, including at least one measurement taken using ultrasound imaging, as part of quantified information can be identified. One of the quantitative measurements can be compared to a first predetermined standard, included as part of ancillary information to the quantified information, in order to identify a first initial value. Further, another of the quantitative measurements can be compared to a second predetermined standard, included as part of the ancillary information, in order to identify a second initial value. Subsequently, the quantitative information can be correlated with the ancillary information using the first initial value and the second initial value to determine a final value that is predictive of a disease state of the subject.

Abstract: A non-transitory computer-readable recording medium stores therein a learning program that causes a computer to execute a process including: setting each of scores to each of a plurality of sets of unlabeled data with regard to each of labels used in a plurality of sets of labeled data based on a distance of each of the plurality of sets of unlabeled data with respect to each of the labels; and causing a learning model to learn using a neural network by using the plurality of sets of labeled data respectively corresponding to the labels of the plurality of sets of labeled data, and the plurality of sets of unlabeled data respectively corresponding to the scores of the plurality of sets of unlabeled data with regard to the labels.

Abstract: Embodiments of the disclosure provide systems and methods for generating a report based on a medical image of a patient. An exemplary system includes a communication interface configured to receive the medical image acquired by an image acquisition device. The system may further include at least one processor. The at least one processor is configured to automatically determine keywords from a natural language description of the medical image generated by applying a learning network to the medical image. The at least one processor is further configured to generate the report describing the medical image of the patient based on the keywords. The at least one processor is also configured to provide the report for display.

Abstract: A structured 3D model of a real-world object is generated from a series of 2D photographs of the object, using photogrammetry, a keypoint detection deep learning network (DLN), and retopology. In addition, object parameters of the object are received. A pressure map of the object is then generated by a pressure estimation DLN based on the structured 3D model and the object parameters. The pressure estimation DLN was trained on structured 3D models, object parameters, and pressure maps of a plurality of objects belonging to a given object category. The pressure map of the real-world object can be used in downstream processes, such as custom manufacturing.

Abstract: A method for training a neural network for triggering an input signal in a measurement device is provided. The method comprises the steps of providing a trigger type and/or trigger parameter from a cloud server hosting the neural network via a network to the measurement device, triggering the input signal based on the trigger type and/or trigger parameter received in the measurement device, and collecting trigger feedback information from the measurement device at the neural network to train the neural network.