Abstract: Systems, computer program products, and methods are described herein for character recognition in a digital image processing environment. The present invention is configured to electronically retrieve one or more documents from a document repository, wherein the one or more documents are in an image format; initiate one or more image super resolution algorithms on the one or more documents; generate, based on at least the one or more image super resolution algorithms, one or more high-resolution images associated with each of the one or more documents; initiate one or more image bottleneck ensembles (IBE) algorithms on the one or more high-resolution images; extract, using the one or more IBE algorithms, one or more features associated with the one or more high resolution images; and store the one or more features extracted from the one or more high resolution images in a feature repository.

Abstract: Disclosed is a display apparatus. The display apparatus includes a communication interface that receives an image from an external electronic device, a display that displays the image, and a processor, wherein the processor generates a user interface (UI) mask including probability information that a plurality of areas included in the image correspond to a UI, by using a convolutional neural network (CNN) algorithm, identifies a UI area included in the image by using the UI mask, identifies a text area included in the UI area, and recognizes text included in the text area.

Abstract: An imaging processing part 131 executes first imaging processing of causing a first illuminating part to emit structured light from a first direction to a measurement target, causing an imaging part 120 to generate image data, and causing a buffer memory 133 to store therein the generated image data. A computing processing part 132 executes first computing processing of generating, height data corresponding to the first direction. Concurrently with the first computing processing, the imaging processing part 131 executes second imaging processing of causing the second illuminating part to emit structured light from a second direction to the measurement target, causing the imaging part 120 to generate image data, and causing a buffer memory 134 to store therein the generated image data. The computing processing part 132 executes second computing processing of generating height data corresponding to the second direction.

Abstract: A gesture detection method, a gesture processing device, and a computer readable storage medium. The gesture detection method includes: performing a shrinking process and a background modeling on a first frame of original image, to generate a first frame of background image; determining a motion region of the first frame of background image based on the first frame of background image; determining a first gesture detection area in the first frame of original image according to the motion region of the first frame of background image; and performing a gesture detection within the first gesture detection area.

Abstract: A method for clip selection includes receiving through an interface to a medical imaging device, a selection of a diagnostic procedure and a target portion of a mammalian body. Thereafter, the device acquires video clip imagery of the target portion and stores the video clip imagery in an image store. Each video clip of the video clip imagery is then image processed to determine a view and a quality of each video clip and a rule is retrieved from a rules base corresponding to the selected diagnostic procedure and target portion. In this regard, the rule specifies a requisite view and quality of the video clip imagery. Finally, the retrieved rule is applied to the video clip imagery as a filter to produce a subset of video clip imagery satisfying the specified requisite view and quality and the subset of video clip imagery is stored in the image store.

Abstract: A method for clip selection includes receiving through an interface to a medical imaging device, a selection of a diagnostic procedure and a target portion of a mammalian body. Thereafter, the device acquires video clip imagery of the target portion and stores the video clip imagery in an image store. Each video clip of the video clip imagery is then image processed to determine a view and a quality of each video clip and a rule is retrieved from a rules base corresponding to the selected diagnostic procedure and target portion. In this regard, the rule specifies a requisite view and quality of the video clip imagery. Finally, the retrieved rule is applied to the video clip imagery as a filter to produce a subset of video clip imagery satisfying the specified requisite view and quality and the subset of video clip imagery is stored in the image store.

Abstract: Embodiments may provide techniques that provide identification of images that can provide reduced resource utilization due to reduced sampling of video frames for visual recognition. For example, in an embodiment, a method of visual recognition processing may be implemented in a computer system comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor, the method comprising: coarsely segmenting video frames of video stream into a plurality of clusters based on scenes of the video stream, sampling a plurality of video frames from each cluster; determining a quality of each cluster, re-clustering the video frames of video stream to improve the quality of at least some of the clusters.

Abstract: An image processing apparatus (12) has a processing device (122) for executing, on a first image (111w) captured by a first imaging device (11w) imaging a first imaging area and a second image (111t) captured by a second imaging device (11t) imaging a second imaging area, an image recognition processing for recognizing a target in the first image and the second image, the processing device executes the image recognition processing on a non-overlapped image part (113w) of the first image without executing it on a overlapped image part (112w) of the first image when the processing device executes the image recognition processing on the first image, the non-overlapped image part includes a non-overlapped area at which the first imaging area does not overlap with the second imaging area, the overlapped image part includes a overlapped area at which the first imaging area overlaps with the second imaging area.

Abstract: A pseudo all-to-all connected system for optical communications are provided. A plurality of nodes are grouped into a node-division multiplexing (NDM) node. An electrical shuffle comprising a plurality of electrical traces connects each port of the plurality of nodes to at least one optical transceiver. The at least one optical transceiver is configured to multiplex a plurality of electrical signals from the plurality of nodes into a plurality of wavelength division multiplexing (WDM) optical signals, the electrical shuffle being configured to route the plurality of electrical signals from each port of the plurality of nodes to form one of a plurality of ordered sequences of signals from the plurality of nodes. A fiber shuffle is configured to route the plurality of WDM optical signals to and from a plurality of NDM connectors.

Abstract: Disclosed is a method and system for splicing and restoring shredded paper based on an extreme learning machine (“ELM”). The method includes: acquiring a shredded paper training sample to be spliced; extracting left and right boundary feature data of the sample; training an ELM neural network model according to the feature data to obtain a trained neural network model (“TNNM”); acquiring a shredded paper test sample to be spliced; extracting feature data of the test sample; selecting a first piece of to-be-spliced shredded paper; selecting, by the TNNM, a shredded piece with a highest degree of coincidence with the first piece; determining whether the shredded piece is correctly spliced to the first piece; if yes, splicing shredded paper until all shredded paper is spliced and restored; if not, adopting manual marking, and continuing to select, by the TNNM, shredded paper with a highest degree of coincidence with the first piece.

Abstract: The invention provides, in some respects, a digital data processing method of identifying a person of interest in a video stream. The method, which executes on a digital data processing system including one or more digital data processing devices in communications coupling with one another, includes detecting using a detector and without using a facial recognizer one or more faces in a video stream. It further includes using a tracker to associate, without using a facial recognizer, one or more of the detected faces with a same apparent individual, and scoring, again, without using a facial recognizer, each of the detected faces that are associated with the same apparent individual. The method further includes applying selected ones of the scored detected faces of the same apparent individual to a facial recognizer to identify a person of interest, where selection is based on scores of the detected faces.

Abstract: Vehicle alert and control systems and methods taking into account a detected road friction at a following vehicle and a predicted road friction by the following vehicle. The detected road friction between the following vehicle tires and the road surface may be assessed using a variety of methodologies and is used to compute a critical safety distance between the following vehicle and the preceding vehicle and a critical safety speed of the following vehicle. The predicted road friction ahead of the following vehicle may also be assessed using a variety of methodologies (lidar, camera, and cloud-based examples are provided) and is used to compute a warning safety distance between the following vehicle and the preceding vehicle and a warning safety speed of the following vehicle. These functionalities may be applied to vehicle/stationary object warning and response scenarios as well.

Abstract: A system for detecting clouds and cloud shadows is described. In one approach, clouds and cloud shadows within a remote sensing image are detected through a three step process. In the first stage a high-precision low-recall classifier is used to identify cloud seed pixels within the image. In the second stage, a low-precision high-recall classifier is used to identify potential cloud pixels within the image. Additionally, in the second stage, the cloud seed pixels are grown into the potential cloud pixels to identify clusters of pixels which have a high likelihood of representing clouds. In the third stage, a geometric technique is used to determine pixels which likely represent shadows cast by the clouds identified in the second stage. The clouds identified in the second stage and the shadows identified in the third stage are then exported as a cloud mask and shadow mask of the remote sensing image.

Abstract: Disclosed herein is an artificial intelligence apparatus for recognizing at least one object, comprising: a memory configured to store a plurality of recognition models for generating identification information corresponding to the object from image data; and a processor configured to: obtain image data for the object, generate first identification information corresponding to the object from the image data using a default recognition model composed of at least one or more of the plurality of recognition models, measure a confidence level for the first identification information, obtain the first identification information as a recognition result of the object if the confidence level is equal to or greater than a first reference value, and obtain second identification information corresponding to the object from the image data as a recognition result of the object using a compound recognition model composed of at least one or more of the plurality of recognition models if the measured confidence level is less

Abstract: The present disclosure relates to an optical line terminal device. The optical line terminal device includes a data center point of presence module, one or more access point of presence modules and one or more aggregation point of presence modules. The data center point of presence module includes a first region and a second region. The first region includes a leaf and spine fabric and a top-of-rack architecture. The second region includes compute infrastructure and storage infrastructure. Further, the one or more access point of presence modules include optical line terminal-Gigabit Passive Optical Networks access input/output and Metro Ethernet Access input/output. The one or more aggregation point of presence include access input/output hardware abstraction, limited compute infrastructure and multi-protocol label switching transfer router.

Abstract: Disclosed are a learning data generation method and apparatus needed to learn animation characters on the basis of deep learning. The learning data generation method needed to learn animation characters on the basis of deep learning may include collecting various images from an external source using wired/wireless communication, acquiring character images from the collected images using a character detection module, clustering the acquired character images, selecting learning data from among the clustered images, and inputting the selected learning data to an artificial neural network for character recognition.

Abstract: A mode demultiplexing hybrid (MDH) that integrates mode demultiplexing, local oscillator power splitting, and optical 90-degree hybrid using multi-plane light conversion (MPLC). Reflective cavity and transmissive systems are disclosed. The MDH may fine advantageous application as the optical front end for a coherent receiver in a space-division multiplexing (SDM) system.

Abstract: An optical communication system that comprises a transmitter adapted to generate a signal by modulating a transmission data as low power consumption symbols of an amplitude modulation format and a monitoring data (MD) as high power consumption symbols of the amplitude modulation format, the MD comprising at least one transmitter parameter and/or at least one receiver parameter of communicating the transmission data. A binary logarithm of a total number of the low power consumption symbols and the high power consumption symbols is a non-integer.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating, transmitting, directing, receiving, and processing optical subcarriers. In some implementations, a system includes a Tier 1 switch that supplies a plurality of data channels; a transmitter that receives the plurality of data channels, the transmitter including an optical modulator that supplies a plurality of optical subcarriers based on the plurality of data channels; an optical platform that receives the plurality of optical subcarriers, the optical platform having a plurality of outputs, each of which supplying at least one of the plurality of subcarriers; a plurality of receivers, each receiving one or more of the plurality of optical subcarriers and supplying one or more of the plurality of data channels; and a plurality of servers, each of which receiving one or more of the plurality of data channels.

Abstract: Embodiments for personalizing operations of an image capturing device by a processor. A combination of one or more objects and features along with associated settings of the image capturing device captured in an image may be classified. One or more personalized patterns of the settings of the image capturing device may be determined according to the classifying. The one or more personalized patterns of the settings of the image capturing device may be applied for capturing a subsequent image.