Abstract: Methods and systems for digitally reconstructing a patient tissue sample are described herein. In one embodiment, the method may include projecting a first structured light pattern onto the patient tissue sample, receiving a first reflection of the first structured light pattern from the patient tissue sample, and reconstructing the patient tissue sample based on the first reflection and the projected first structured light pattern. In another embodiment, the system may include a projector adapted or configured to project the first structured light onto the patient tissue sample, a charge-coupled device (CCD) adapted or configured to receive the first reflection from the patient tissue sample, and a reconstruction device adapted or configured to reconstruct the patient tissue sample based on the first reflection and the projected first structured light pattern.

Abstract: In many real-life applications, ample amount of examples from one class are present while examples from other classes are rare for training and learning purposes leading to class imbalance problem and misclassification. Methods and systems of the present disclosure facilitate generation of an extended synthetic rare class super dataset that is further pruned to obtain a synthetic rare class dataset by maximizing similarity and diversity in the synthetic rare class dataset while preserving morphological identity with labeled rare class training dataset. Oversampling methods used in the art result in cloning of datasets and do not provide the needed diversity. The methods of the present disclosure can be applied to classification of noisy phonocardiogram (PCG) signals among other applications.

Abstract: A microscope comprises a microscope stand, a camera for recording microscope images and a computing device, which is configured to carry out image processing of the recorded microscope images. The computing device is configured to: define relevant image structures; localize relevant image structures in the microscope images; derive stitching parameters from locations of the relevant image structures; and create a result image with the aid of the microscope images, with the stitching parameters being taken into account. Moreover, a corresponding method is described.

Abstract: Methods, systems, and computer program products for learning models for entity resolution using active learning are provided herein. A computer-implemented method includes determining a set of data items related to a task associated with structured knowledge base creation, and outputting the set of data items to a user for labeling. Such a method also includes generating, based on a user-labeled version of the set of data items, a candidate model for executing the task, and one or more generalized versions of the candidate model. Additionally, such a method can also include generating a final model based on one or more iterations of analysis of the candidate model and analysis of the one or more generalized versions of the candidate model, and performing the task by executing the final model on one or more datasets.

Abstract: An information processing method includes acquiring a first prediction result by inputting evaluation data to a first model; determining an anomaly in the first prediction result based on the first prediction result and reference information; acquiring a second model based on the determination result; acquiring a second prediction result by inputting the evaluation data to the second model; determining an anomaly in the second prediction result based on the second prediction result and the reference information; acquiring a third model based on the determination result; acquiring a third prediction result by inputting the evaluation data to the third model; determining an anomaly in the third prediction result based on the third prediction result and the reference information; and if the anomaly in the third prediction result is recognized as being identical to the anomaly in the first prediction result, outputting information about a training limit of the first model.

Abstract: The disclosure relates to a method for scanning microscopy wherein a specimen is scanned simultaneously with a plurality of illumination spots of an excitation light. The light emitted by one specimen location irradiated with one illumination spot is detected independently of the light emitted by another specimen location illuminated with another illumination spot. A microscopic image of the specimen can be compiled from the emitted light detected for the different specimen locations. The method provides that the intensities of the different illumination spots are set independently of one another, and in that the illumination spots are guided over the specimen one after another in a scan line. The disclosure additionally relates to a scanning microscope.

Abstract: Digital data processing circuitry is described that uses combinatorial logic hardware and sequential logic hardware to process one or more inputs. For each input a periodic sequence is generated that is based at least in part on a value of the input and a weight value. A match is determined at an event time when the periodic sequence(s) matches a corresponding arbitrary reference pattern. The digital data processing circuitry may be implemented as an integrated circuit as part of an interconnected network of devices that may be trained and subsequently used for recognition or other complex data processing tasks.

Abstract: Disclosed embodiments relate to systems and methods for locating, measuring, counting or aiding in the handling of drill pipes 106. The system 100 comprises at least one camera 102 capable of gathering visual data 150 regarding detecting, localizing or both, pipes 106, roughnecks 116, elevators 118 and combinations thereof. The system 100 further comprises a processor 110 and a logging system 114 for recording the gathered visual data 150. The method 200 comprises acquiring visual data 150 using a camera 106, analyzing the acquired data 150, and recording the acquired data 150.

Abstract: A data coding method includes determining a length of a current first bit-rate-control-unit data frame in to-be-transmitted data, and the length of the first bit-rate-control-unit data frame is less than or equal to a length of a group of pictures (GOP) data frame. The method also includes determining a first target bit rate of the first bit-rate-control-unit data frame according to the length of the first bit-rate-control-unit data frame, a target bit rate of the to-be-transmitted data, and a frame rate of the to-be-transmitted data and, when a first difference value between a real bit rate of a second bit-rate-control-unit data frame and a second target bit rate of the second bit-rate-control-unit data frame is greater than zero, adjusting the first target bit rate according to the first difference value, and coding the first bit-rate-control-unit data frame according to the adjusted first target bit rate.

Abstract: An image coding method includes coding a motion vector difference indicating a difference between the motion vector and a predicted motion vector, wherein the coding includes: coding a first portion that is a part of a first component which is one of a horizontal component and a vertical component of the motion vector difference; coding a second portion that is a part of a second component which is different from the first component and is the other one of the horizontal component and the vertical component; coding a third portion that is a part of the first component and is different from the first portion; coding a fourth portion that is a part of the second component and is different from the second portion; and generating a code string which includes the first portion, the second portion, the third portion, and the fourth portion in the stated order.

Abstract: A three-dimensional display device configured to display a main image and an additional image on a screen includes a display region candidate decider that decides one candidate region from a plurality of region candidates for the additional image to be superimposed on the main image on the screen, a depth suitability determiner that determines whether a difference between a depth of the main image displayed at a boundary region and a depth of the additional image is within a predetermined tolerance range, and an image composer that, when the difference in depth between the depth of the main image displayed at the boundary region and the depth of the additional image is within the tolerance range, superimposes the additional image upon the main image at the candidate region, thereby composing a composite image of the main image and the additional image, and displays the composite image on the screen.

Abstract: The present disclosure provides a 3D display device and a working method of the same, the 3D display device includes a display panel, a lens unit, an acquiring component and an adjusting component, the acquiring component is configured to acquire current positions of eyes of a viewer, and the adjusting component is configured to adjust a signal for driving the display panel according to the current positions so that display information of the display panel received by the eyes of the viewer at the current positions is the same as display information of the display panel received by the eyes of the viewer at preset positions.

Abstract: The disclosed subject matter is directed to employing machine learning models configured to predict 3D data from 2D images using deep learning techniques to derive 3D data for the 2D images. In some embodiments, a method is provided that comprises receiving, by a system comprising a processor, a panoramic image, and employing, by the system, a three-dimensional data from two-dimensional data (3D-from-2D) convolutional neural network model to derive three-dimensional data from the panoramic image, wherein the 3D-from-2D convolutional neural network model employs convolutional layers that wrap around the panoramic image as projected on a two-dimensional plane to facilitate deriving the three-dimensional data.

Abstract: In a system and method for determining vital sign information of a subject the subject is illuminated with radiation, and radiation reflected from the subject is received. A region of interest is located in a first phase. Said illumination is controlled to locally illuminate, in a second phase, the located region of interest with radiation allowing determination of vital sign information. Finally, vital sign information of the subject is determined from the radiation reflected from said region of interest and detected in said second phase.

Abstract: The disclosed subject matter is directed to employing machine learning models configured to predict 3D data from 2D images using deep learning techniques to derive 3D data for the 2D images. In some embodiments, a method is provided that comprises employing, by a system comprising a processor, one or more three-dimensional data from two-dimensional data (3D-from-2D) neural network models to derive three-dimensional data from one or more two-dimensional images captured of an object or environment from a current perspective of the object or environment viewed on or through a display of the device. The method further comprises, determining, by the system, a position for integrating a graphical data object on or within a representation of the object or environment viewed on or through the display based on the current perspective and the three-dimensional data.

Abstract: A server system and method is for facilitating garment creation. A processor and storage device are configured to receive and store designed digital garment or garment parts for selection, approval and/or inclusion into a digital garment. A designer interface is accessible over a network and is configured to view, approve, select and place two or more of the digital garment parts together to form a digital garment to store in the storage device. An online purchase system is configured to access the storage device to select and purchase the digital garment from a plurality of available digital garments.

Abstract: A multi-headed camera assembly includes a base comprising a plurality of tracks, a plurality of image sensor assemblies each comprising a support mechanism configured to allow a quick and efficient assembly of a lens assembly within a housing and each removably coupled to the base by a corresponding support frame among a plurality of support frames. Each support frame comprises a guide member for guiding tilt movement of a corresponding image sensor assembly and a support base movably coupled to a corresponding track so as to accomplish pan movement of the corresponding image sensor assembly. The multi-headed camera assembly further includes a surface mount mechanism, an in-ceiling mount mechanism, or a pendant mount mechanism so that the multi-headed camera assembly can be removably mounted to a surface, mounted into a ceiling, or connected to a pendant base.

Abstract: The disclosed subject matter is directed to employing machine learning models configured to predict 3D data from 2D images using deep learning techniques to derive 3D data for the 2D images. In some embodiments, a method is provided that comprises receiving, by a system operatively coupled to a processor, a two-dimensional image, and determining, by the system, auxiliary data for the two-dimensional image, wherein the auxiliary data comprises orientation information regarding a capture orientation of the two-dimensional image. The method further comprises, deriving, by the system, three-dimensional information for the two-dimensional image using one or more neural network models configured to infer the three-dimensional information based on the two-dimensional image and the auxiliary data.

Abstract: A method of displaying surveillance video streams is provided that includes receiving surveillance video streams generated by a plurality of video cameras, and displaying a selected subset of the surveillance video streams in a summary view on at least one display device, wherein, for each surveillance video stream in the summary view, only a relevant portion of each frame in the surveillance video stream is displayed, and wherein a relevant portion is a subset of a frame for at least some of the surveillance video streams in the summary view.

Abstract: Various embodiments include a system and method that enhance the visualization of selected individual images from a real-time scan. The method can include acquiring ultrasound image data at an ultrasound system. The method may include processing the acquired ultrasound image data according to cine sequence processing parameters to generate a cine sequence. The cine sequence includes a plurality of frames, each of the frames having a first resolution. The method can include receiving a trigger. The method may include processing the acquired ultrasound image data according to still image processing parameters in response to the trigger to generate a still image. The still image has a second resolution that is higher than the first resolution.