Abstract: Devices, systems and methods are provided to improve pairing between two devices by employing an inductive antenna circuit (e.g., 13.56 MHz) in addition to another wireless communication antenna circuit (e.g., 2.4 GHz) and a pairing protocol to minimize pairing between unintended devices. Communications via inductive antenna circuit (e.g., 13.56 MHz) require that the devices to be paired to be in close proximity to each other, which increases the likelihood of intended pairing between these devices. When the inductive pulses of the first device are detected by the second device, the second device commences advertising signals with time stamps. The inductive pulses and the time stamps facilitate synchronizing scanning windows of the first device with the advertising signals of the second device to lessen the likelihood of interference of advertising pulses from an unintended device.

Abstract: Various embodiments described herein relate to techniques for computing dimensions of an object using multiple range images. In this aspect, the multiple range images are captured from selective locations and satisfy a pre-defined criterion. In accordance with various embodiments, at least a pair of 3D points are identified from the multiple range images, which correspond to at least one geometric feature on a surface of the object. In this regard, a correspondence score is estimated for the identified at least one pair of 3D points. The correspondence score is then utilized for registering the at least one pair of 3D points. Based in part on the registration of the 3D points and 3D point clouds retrieved from the captured images, the dimensions of the object are computed.

Abstract: A system and method for learning and associating reliability and confidence corresponding to a model's predictions by examining the support associated with datapoints in the variable phase space in terms of data coverage, and their impact on the weights distribution. The approach disclosed herein examines the impact of minor perturbations on a small fraction of the training exemplars in the variable phase space on the weights to understand whether the weights remain unperturbed or change significantly.

Abstract: The disclosed system, method and computer-readable medium provide for a first wireless network, a second wireless network, a premises device and a mobile device. The first and second wireless networks are configured to operate according to respective first and second wireless networking standards, where the first and second wireless networking standards are incompatible. The mobile device is configured to communicate according to the first wireless network standard. The premises gateway device includes a transmitter for the second wireless networking standard.

Abstract: A magnetic resonance imaging (MRI) system includes control and analysis circuitry having programming to acquire magnetic resonance (MR) data using coil elements of the MRI system, analyze the MR data, and reconstruct the MR data into MR sub-images. The system also includes a trained neural network associated with the control and analysis circuitry to transform the MR sub-images into a prediction relating to a presence and extent of motion corruption in the MR sub-images. The programming of the control and analysis circuitry includes instructions to control operations of the MRI system based at least in part on the prediction of the trained neural network.

Abstract: Techniques for performing learnt image compression and object detection using compressed image data are described. A system may perform image compression using an image compression model that includes an encoder, an entropy model, and a decoder. The encoder, the entropy model, and the decoder may be jointly trained using machine learning based on training data. After training, the encoder and the decoder may be separated to encode image data to generate compressed image data or to decode compressed image data to generate reconstructed image data. In addition, the system may perform object detection using a compressed object detection model that processes compressed image data generated by the image compression model. For example, the compressed object detection model may perform partial decoding using a single layer of the decoder and perform compressed object detection on the partially decoded image data.

Abstract: The disclosure provides an image processing method and an image processing device. The method includes: obtaining a specific block from a specific block group of a specific image, wherein the specific block group includes blocks; compressing the specific block as a specific stream based on a predetermined compression ratio; when a length of the specific stream is not shorter than a predetermined block length, dividing the specific stream into a first sub-stream and a second sub-stream; storing the first sub-stream into a specific private block of a plurality of private blocks; finding an idle chunk out of shared chunks shared by the blocks; if the idle chunk is enough for storing the second sub-stream, storing the second sub-stream into the idle chunk and using a chunk usage information to record a number of the idle chunk.

Abstract: Systems, methods, and computer-readable media are provided for an autonomous and fully automated method of validating multi-signature decoys that are configured to release infrared flares at multiple points after launch. In one aspect, a method includes capturing, using at least one image capturing device, raw image data of a launched decoy, the decoy having one or more segments configured to be released after launch and automatically processing the raw image data to (1) identify a release point for each of the one or more segments and (2) identify an infrared signature associated with each release point. The method further includes generating a visual display of the release point(s) of the one or more segments and the infrared signature(s) originating from the release point(s).

Abstract: Segmentation of three dimensional objects may be implemented using a neural network model, a clustering module, a factorization module, and a geometric fitting module. The neural network model is configured to analyze point cloud data for a geographic region and assign probability values outputted from the neural network to points in the point cloud data. The clustering module is configured to group a subset of the probability values based on relative locations of the assigned points in the point cloud data. The factorization module is configured to factor a matrix with the subset of the clustered probability values to assign a line for a three dimensional object of the geographic region. The geometric fitting module is configured to fit at least one predetermined shape for the three dimensional object to the point cloud data based at least on the assigned line.

Abstract: A computer implemented method and system for correcting error produced by Optical Character Recognition (OCR) of text contained in an image encoded document. An error model representing frequency and type of errors produced by Optical Character Recognition Engine is generated. An OCR character string generated by OCR is retrieved. A user-defined pattern of a plurality of character strings is retrieved, where each character string represents a possible correct representation of characters in the OCR character string. The OCR character string is compared to each of the above generated character strings and a ‘likelihood score’ is calculated based on the information from the error model. The character string with the highest ‘likelihood score’ is presumed to be the corrected version of the OCR character string.

Abstract: Disclosed herein is a method and device for identifying bold text in a digital document. The system receives image of digital document which comprises text. The system applies bounding box for each text in the image and scans predefined number of lines in each bounding box to identify width values of pixels. Thereafter, system identifies most occurring width value of pixels among the width values of pixels in each bounding box. The most occurring width value of pixels in each bounding box is identified as box width of corresponding bounding box. The system compares box width of each bounding box with threshold box width. If box width is greater than threshold box width, system identifies text of the bounding box whose box width exceeds threshold box width as bold text. The present disclosure efficiently identifies bold text in digital document based on width values of pixels with less computational power.

Abstract: Disclosed are an electronic device and a method of short range wireless communication in an electronic device. The method of operating the electronic device may include: when a cover is connected to the electronic device through a short range wireless communication connection, determining generation of an event related to the cover. The method further comprises, when the event is generated, supplying power to the cover through wireless communication, when the cover is driven by the supplied power, transmitting event information to the cover through the short range wireless communication connection to display the information related to the generated event on the cover, and, when an operation of the cover according to the event is completed, switching to a standby mode after releasing the short range wireless communication connection with the cover.

Abstract: The network system triggers registration of the start of a transport journey in response to a communication of a transport user device and a transport provider device with each other, performs a continuous coordinated proximity monitoring to verify the identity of a transport user and a transport provider vehicle, and triggers registration of the end of the transport journey through communication of the transport user device and the transport provider device with each other.

Abstract: A method for determining a second quantizer for quantizing digital images, wherein the second quantizer is determined for a specified number of levels, which is at least two. For the determination, a first quantizer with a lower number of levels than the specified one is taken into consideration. Furthermore, a method for coding an image comprising a plurality of pixels, a computer-readable medium, an apparatus, which implements at least two quantizers as a digital circuit and a digital camera with such an apparatus is disclosed.

Abstract: Apparatus, systems, methods, and articles of manufacture are disclosed for assigning a color to a point in three-dimensional (3D) video. An example system includes an aggregator to access data from real cameras, the data including spatial coordinates and colors for a plurality of two-dimensional (2D) points in video data captured by the real cameras. The aggregator is to create a point cloud correlating the 2D points to the 3D points. The example system also includes a selector to select a subset of the real cameras based on a position of a virtual camera. In addition, the example system includes an analyzer to: select a point from the point cloud in a field of view of the virtual camera; select one of the subset of real cameras having a non-occluded view of the point and a perspective closest to that of the virtual camera; and assign a color to the point based on color data associated with the selected one of the real cameras.

Abstract: A method for a terminal mitigating interference in a wireless communication system according to an embodiment of the present invention comprises the steps of: receiving a first message having a previously configured pattern from a serving base station communicating cooperatively to control interference with at least one adjacent base station; triggering a common reference signal (CRS) interference mitigation function of the terminal in response to the first message in order to mitigate interference due to a CRS transmitted from the at least one adjacent base station; and cancelling interference due to the CRS on the basis of the CRS interference mitigation function, and receiving data.

Abstract: A transceiver includes a receive path including a low noise amplifier and a first switch coupled between the low noise amplifier and ground, a first transmit path including a low power amplifier and a second switch coupled between the low power amplifier and a main signal path, and a second transmit path including a high power amplifier and a third switch coupled between the main signal path and ground. The receive path is active when the first, second, and third switches are in an open position, the first transmit path is active when the first switch is in a closed position, the second switch is in the closed position, and the third switch is in the open position, and the second transmit path is active when the first switch and the third switch are in the closed position, and the second switch is in the open position.

Abstract: A demultiplexing apparatus according to the present disclosure includes an amplifier that amplifies transmission signals in three or more communication bands having different frequency bands; multiple signal paths which are commonly provided for an output terminal of the amplifier and on which the signals in the corresponding communication bands are propagated; and multiple transmission-reception filters which are provided on the multiple signal paths, and each of which isolates a transmission signal and a reception signal of the corresponding communication band from each other. The gains of the amplifier in the frequency bands of multiple reception signals are smaller than the gains of the amplifier in the frequency bands of multiple transmission signals.

Abstract: The present disclosure relates to a tag-based font recognition system that utilizes a multi-learning framework to develop and improve tag-based font recognition using deep learning neural networks. In particular, the tag-based font recognition system jointly trains a font tag recognition neural network with an implicit font classification attention model to generate font tag probability vectors that are enhanced by implicit font classification information. Indeed, the font recognition system weights the hidden layers of the font tag recognition neural network with implicit font information to improve the accuracy and predictability of the font tag recognition neural network, which results in improved retrieval of fonts in response to a font tag query. Accordingly, using the enhanced tag probability vectors, the tag-based font recognition system can accurately identify and recommend one or more fonts in response to a font tag query.

Abstract: A communication device includes a first processing unit that sends a first command to start an activation processing. The communication device also includes a second processing unit that receives the first command from the first processing unit. In addition, the communication device includes an interface between the first processing unit and the second processing unit. The first processing unit activates the interface at a predetermined interface level from among a plurality of interface levels. The second processing unit starts an application in accordance with the activated interface level. The first processing unit and the second processing unit exchange data by the activated application. The first processing unit and the second processing unit perform a deactivation processing of the activated interface.