Abstract: Techniques of automatic image classification and modification in computing systems are disclosed herein. In one embodiment, a method includes scanning an inbox on email servers for emails containing image files. Upon detecting that an email in the inbox contains an image file, the method includes retrieving an identification photo of a user from a data store. The method also includes determining, via facial recognition, whether the image file in the email contains at least a partial image of the user based on the retrieved identification photo. In response to determining that the image file in the email contains at least a partial image of the user, a metadata value is inserted into the image file indicating that the image file contains at least a partial image of the user before the image file is stored in the inbox on the one or more email servers.

Abstract: A surveillance camera includes an imaging unit configured to output a video frame, and a control unit configured to set a search range in the video frame and to extract a tracking-target image by using a feature quantity of an image in the search range. In a case where an object image other than the tracking target is contained in the search range, the control unit masks a feature quantity of the object image and extracts the tracking-target image.

Abstract: Disclosed herein are an apparatus for automatic ultrasound diagnosis of liver steatosis using feature points in an ultrasound image, which can automatically determine a grade of liver steatosis, which is difficult to determine visually, through extraction from an image acquired by medical imaging, and a remote medical diagnosis method using the same.

Abstract: A tooth virtual editing method comprises: constructing a three-dimensional image basic database of a human oral cavity; acquiring three-dimensional image data of a user oral cavity, performing image pattern recognition on the three-dimensional image data according to the stored three-dimensional image basic database, recognizing an object to which the image data belongs, and establishing an object annotation system of the user oral cavity, wherein the object contains a block and/or an entity; and performing virtual editing on the object according to the established object annotation system of the current user, and displaying an updated three-dimensional image of the teeth.

Abstract: A monitoring system or tracking system may include an input port and a controller in communication with the input port. The input port may receive video from one or more image capturing devices. The image capturing device is optionally part of the monitoring system and in some cases includes at least part of the controller. The controller may be configured to receive video via the input port and identify a subject within frames of the video relative to a background within the frames. Further, the controller may be configured to identify dimensions, posture, hand location, feet location, twisting position/angle, and/or other parameters of the identified subject in frames of the video and determine when the subject is performing a task. Based on the dimensions and/or other parameters identified or extracted from the video during the predetermined task, the controller may output via the output port assessment information.

Abstract: Systems and methods for selectively processing image studies with an artificial intelligence system. One system includes an electronic processor configured to select an image study awaiting review and update a workflow status of the image study to a first status indicating that the image study has been claimed for review by the artificial intelligence system. The electronic processor is also configured to apply at least one of the plurality of rules to the image study to determine whether the image study is applicable for processing by the artificial intelligence system, and, in response to determining the image study is not applicable for processing by the artificial intelligence system based on the at least one of the plurality of rules, update the workflow status associated with the image study to a second status to make the image study available for claiming by a manual reviewer or another artificial intelligence system.

Abstract: A system and method for distributed surveillance of an area to monitor a process and visual effects of the process. Exemplary methods include, among others, asset effectiveness, issue identification and prioritization, workflow optimization, monitoring, estimation, verification, compliance, presentation, and/or identification for a given process. Such application may include, but are not limited to, manufacturing, quality control, supply chain management, and safety compliance.

Abstract: A body language system for determining a body language message of a living being in a context comprising an artificial intelligence system, said AI system running a computer program that: retrieves an image of said living being showing body language; labels said living being in said image, resulting in a labeled living being; determines said context from said image using a trained machine learning model; determines a baseline body language of said labeled living being from said image using a trained machine learning model; adapts a trained machine learning model of said AI system using said baseline body language and said context; applies the adapted trained machine learning model of said AI system to the one image for categorizing said body language resulting in a category, and applying said category for determining said body language message.

Abstract: The present disclosure relates to an information processing apparatus, an information processing method, and a vegetation management system each capable of managing vegetation in such a manner as to maintain a high quality state and achieve uniform growth. In a vegetation management system, an image acquiring apparatus acquires an image in which vegetation corresponding to a target of management is captured. An analysis unit analyzes the image as at least input information and outputs a predetermined analysis result. Then, a determination unit determines work contents to be performed for the vegetation, according to the analysis result. A work apparatus performs a process for executing work for the vegetation according to the work contents. For example, the present technology is applicable to a management system that manages natural grass.

Abstract: A patient's healthcare experience may be enhanced utilizing a system that automatically recognizes the patient based on one or more images of the patient and generates personalized medical assistance information for the patient based on electronic medical records stored for the patient. Such electronic medical records may comprise imagery data and/or non-imagery associated with a medical procedure performed or to be performed for the patient. As such, the imagery and/or non-imagery data may be incorporated into the personalized medical assistance information to provide positioning and/or other types of diagnostic or treatment guidance to the patient or a service provider.

Abstract: A medical image processing apparatus includes a medical image acquisition unit that acquires the medical image including a subject image, a medical image analysis result acquisition unit that acquires an analysis result obtained by analyzing the medical image, a display unit that displays at least one medical image and at least information on presence or absence of a treatment tool or a type of a treatment tool in the analysis result acquired by the medical image analysis result acquisition unit, and an input receiving unit that receives an input regarding whether or not the information on presence or absence of a treatment tool or a type of a treatment tool included in the analysis result is correct.

Abstract: A master control system for a remote-sensing satellite image processing device, the system including: a master control management module, a first FPGA module, and a second FPGA module. The master control management module is in connection and communication with the first FPGA module, the second FPGA module, and a housekeeping computer. The first FPGA module is in connection and communication with the second FPGA module and a remote-sensing satellite image processing device. The master control management module is adapted to perform assignment of tasks. The first FPGA module is adapted to communicate with a processor in the satellite image processing device, monitor an operation state of the satellite image processing device, send the operation state information to the master control management module, receive a task assignment command issued by the master control management module, and transmit the task assignment command to the satellite image processing device.

Abstract: Aspects of the subject disclosure may include, for example, a method comprising obtaining, by a processing system including a processor, first and second models for a structure of an object, based respectively on ground-level and aerial observations of the object. Model parameters are determined for a three-dimensional (3D) third model of the object based on the first and second models; the determining comprises a transfer learning procedure. Data representing observations of the object is captured at an airborne unmanned aircraft system (UAS) operating at an altitude between that of the ground-level observations and the aerial observations. The method also comprises dynamically adjusting the third model in accordance with the operating altitude of the UAS; updating the adjusted third model in accordance with the data; and determining a 3D representation of the structure of the object, based on the updated adjusted third model. Other embodiments are disclosed.

Abstract: A method of generating a color image of a sample includes obtaining a plurality of low resolution holographic images of the sample using a color image sensor, the sample illuminated simultaneously by light from three or more distinct colors, wherein the illuminated sample casts sample holograms on the image sensor and wherein the plurality of low resolution holographic images are obtained by relative x, y, and z directional shifts between sample holograms and the image sensor. Pixel super-resolved holograms of the sample are generated at each of the three or more distinct colors. De-multiplexed holograms are generated from the pixel super-resolved holograms. Phase information is retrieved from the de-multiplexed holograms using a phase retrieval algorithm to obtain complex holograms. The complex hologram for the three or more distinct colors is digitally combined and back-propagated to a sample plane to generate the color image.

Abstract: An image recognition method is provided, including: obtaining a target video including a target object; extracting a target video frame image from the target video; generating a key point video frame sequence comprised of a plurality of key point video frames according to key point information of the object and a plurality of video frames in the target video; extracting dynamic timing feature information of the key point video frame sequence; extracting static structural feature information of the target video frame image; and recognizing an attribute type corresponding to the target object in the target video according to the dynamic timing feature information of the key point video frame sequence and the static structural feature information of the target video frame image.

Abstract: A computer-implemented method for selecting aerial images for image processing to identify Energy Infrastructure (EI) features is provided. The method includes performing image processing on aerial images of a portion of global terrain captured at different times to determine differences in terrain content the captured images. Aerial images are selected for further image processing according to identified differences in terrain content. The selected images are imaged processed via an EI feature recognition type to identify EI features within the images.

Abstract: Systems, methods and computer program products are provided for reading and scoring ultrasound and/or optoacoustic (US/OA) images that include at least one of OA images or US images acquired in connection with an examination for a region of interest (ROI). The system displays a first image that has an interior ROI outline separating an internal zone from a boundary zone. In some aspects, feature scores are obtained in connection with at least the boundary zone and peripheral zone of the first image and the feature scores are applied to a classification model to obtain at least one of a prognostic result or predictive result indicative of a trait of the lesion. In accordance with some aspects, an order in which feature scores are entered is automatically managed to obtain for the at least one of the peripheral zone or the boundary zone before the feature score is obtained for the internal zone.

Abstract: Operations may comprise obtaining a plurality of light detection and ranging (LIDAR) scans of a region. The operations may also comprise identifying a plurality of LIDAR poses that correspond to the plurality of LIDAR scans. In addition, the operations may comprise identifying, as a plurality of keyframes, a plurality of images of the region that are captured during capturing of the plurality of LIDAR scans. The operations may also comprise determining, based on the plurality of LIDAR poses, a plurality of camera poses that correspond to the keyframes. Further, the operations may comprise identifying a plurality of two-dimensional (2D) keypoints in the keyframes. The operations also may comprise generating one or more three-dimensional (3D) keypoints based on the plurality of 2D keypoints and the respective camera poses of the plurality of keyframes.

Abstract: Based on an image from a stationary sensor, a marker displayed on one or more digital displays on a vehicle is detected. A first location and a first orientation of the marker in a coordinate system is determined by analyzing on pixels in the image. Based on a stationary sensor location and orientation from a map, a second location and a second orientation of the vehicle in the coordinate system is determined.

Abstract: Autonomous vehicles and techniques that can be utilized to compress point cloud data and operate on compressed point cloud data are provided. An autonomous vehicle can include a data compression system can configure point cloud data according to a collection of three-dimensional (3D) tiles representative of the region. Each 3D tile can include a portion of the cloud point data, where each point vector in the portion of the cloud point data can be configured relative to a position vector of the 3D tile defined in a coordinate system of the collection of 3D tiles. The data compression system can utilize a fixed-point Q-format representation based on a defined number of bits to compress at least a portion of the point cloud data. The autonomous vehicle also can include a control system that can operate mathematically on compressed point cloud data, without reliance on prior decompression.