A web detection system processes webpage information and performs automated feature extraction of webpages including machine processable information. In an embodiment, the web detection system determines a subset of webpages having a target characteristic by processing markup language. For a webpage of the subset, the web detection system determines that a first image overlaps at least a portion of a second image in the webpage. The web detection system generates an image of the webpage such that the portion of the second image is obscured by the first image. The web detection system determines a graphical feature of the webpage by processing the image, e.g., using optical character recognition. Responsive to determining that the graphical feature corresponds to graphical features of images of a different set of webpages associated with a target entity, the web detection system determines that the webpage is also associated with the target entity.

Systems and apparatuses for capturing an image of a vehicle for which roadside assistance is being requested are provided. The image may be captured by a mobile device and the mobile device may geotag location information to the image. The image and associated geotag location information may then be processed to determine a location of the vehicle and a roadside assistance issue for which service is being requested. The image may be further analyzed to determine a context including, a make, model and/or year of the vehicle, whether special equipment is needed to service the vehicle, whether the vehicle is located in a particular situation (e.g., within a structure, in a ditch, or the like). The information obtained from the image may be used to determine a type of service to provide to the vehicle and to identify one or more service providers to dispatch to the vehicle.

Disclosed are an X-ray imaging system and method, and the system comprises an X-ray source, a high-voltage generator, a collimator, a digital flat-panel detector, and a host computer; a position relationship between a projection area and a subject is visually displayed through a display screen; as an image frame on the screen is directly dragged to a corresponding position of an image of the subject presented on the screen or an area of interest is drawn, the collimator automatically drives a collimating sheet to move and enables the projection area to move to an observation position required by the subject, and information about the area of interest is transmitted to the detector as an input for selecting a response area of automatic exposure control (AEC). The collimator cooperates with digital automatic exposure control (DAEC), so that a strict requirement is no longer existent for patient positioning.

An image recognition device executes a Hilbert scan of frame image data constituting moving-image data to generate one-dimensional spatial image data, and further arrays the one-dimensional spatial image data in a time direction to generate two-dimensional spatio-temporal image data that holds spatial information and temporal information. The image recognition device converts the moving-image data into the two-dimensional spatio-temporal image data while holding the spatial and temporal information. By means of a CNN unit, the image recognition device executes a convolution process wherein a two-dimensional filter is used on the spatio-temporal image data to image-recognize a behavior of a pedestrian who is a recognition object. The image recognition device executes behavioral recognition of the pedestrian that requires a three-dimensional analysis consisting of two dimensions for space and one dimension for time by the image recognition process of the two-dimensional image by the CNN, and estimates a state of the pedestrian.

An imaging apparatus includes: an imaging unit that has a pixel region in which a plurality of pixels is arranged and that reads and outputs a pixel signal from the pixels included in the pixel region; a unit-of-readout controller that controls a unit of readout set as a part of the pixel region: a recognition unit that has learned training data for each of units of readout; a first output unit that outputs a recognition result of recognition performed by the recognition unit for each of the units of readout; a second output unit that outputs the pixel signal to a subsequent stage; and a trigger generator that generates a trigger signal for controlling a first timing at which the first output unit outputs the recognition result and a second timing at which the second output unit outputs the pixel signal.

An imaging apparatus includes: an imaging unit that has a pixel region in which a plurality of pixels is arranged and reads and outputs a pixel signal from the pixels included in the pixel region; a unit-of-readout controller that controls a unit of readout set as a part of the pixel region; a first unit-of-readout setting unit that sets a first unit of readout that is used for reading out the pixel signal from the pixel region for a recognition process that has learned training data for each of the units of readout; a second unit-of-readout setting unit that sets a second unit of readout that is used for reading out the pixel signal from the pixel region so as to output the pixel signal to a subsequent stage; and a mediation unit that performs mediation between the first unit of readout and the second unit of readout.

An imaging apparatus according to an embodiment includes: an imaging unit (10) having a pixel region in which a plurality of pixels is arranged; a readout controller (11) that controls readout of pixel signals from pixels included in the pixel region; a unit-of-readout controller (123) that controls a unit of readout that is set as a part of the pixel region and for which the readout controller performs the readout; and a recognition unit (14) that has learned training data for each of the units of readout. The recognition unit performs a recognition process on the pixel signal for each of the units of readout, and outputs a recognition result which is a result of the recognition process.

A terminal apparatus according to an embodiment includes a solid-state imaging element and a first communication unit. The solid-state imaging element includes an image sensor, an image processing unit, and an output interface. The image sensor converts received light into an image. The image processing unit detects a specific object in the image. The output interface outputs the image. The first communication unit transmits the image output from the output interface. The information processing apparatus includes a second communication unit and a processor. The processor receives an image transmitted from the terminal apparatus with the second communication unit. When the image received with the second communication unit is an image in which the image processing unit has detected a specific object, the processor performs mask processing of masking the specific object.

A system for applying video data to a neural network (NN) for online multi-class multi-object tracking includes a computer programed to perform an image classification method including the operations of receiving a video sequence; detecting candidate objects in each of a previous and a current video frame; transforming the previous and current video frames into a temporal difference input image; applying the temporal difference input image to a pre-trained neural network (NN) (or deep convolutional network) comprising an ordered sequence of layers; and based on a classification value received by the neural network, associating a pair of detected candidate objects in the previous and current frames as belonging to one of matching objects and different objects.

A mobile application for facilitating configuration and installation of networking and extender devices in a local area network utilizes augmented reality to provide configuration guidance information and network information. For configuring the networking device, a camera of the mobile computing device captures an image depicting the networking device, which is displayed on a touchscreen display of the mobile computing device with graphical elements including icons and textual information overlaid on the image to indicate configuration guidance information. Similarly, for installing the extender device, the camera captures image data depicting areas of the premises where the device is being installed and graphical elements are overlaid on the image data indicating network information such as the position of a previously installed networking device as well as the signal strength of wireless signals from the networking device.