284results about How to "Accurate mapping" patented technology

An image guided navigation system for navigating a region of a patient which is gated using ECG signals to confirm diastole. The navigation system includes an imaging device, a tracking device, a controller, and a display. The imaging device generates images of the region of a patient. The tracking device tracks the location of the instrument in a region of the patient. The controller superimposes an icon representative of the instrument onto the images generated from the imaging device based upon the location of the instrument. The display displays the image with the superimposed instrument. The images and a registration process may be synchronized to a physiological event.

A sensor system, method, and computer program product for determining physical characteristics of individual plants within a row located in an agricultural environment is provided. Embodiments of the present invention include, but are not limited to, a sensor assembly including a plurality of emitters and a corresponding plurality of receivers disposed substantially opposite one another such that the receivers may receive a plurality of signals emitted by said emitters to generate a binary profile image of each plant within a row of plants positioned along a row axis. Embodiments of the present invention also include supplementary sensors for determining other plant characteristics including leaf pattern and plant location along the row axis. The method and computer program product embodiments of the present invention may also differentiate selected plants of interest from invasive or weed species using the outputs of the sensor device of the present invention.

Some embodiments provide a novel method for performing a service at a host computer that executes data compute nodes (DCNs). For a data message, the method identifies a service tag and a set of attributes associated with the service tag. The method then uses the identified set of attributes to identify a service rule, and performs a service on the data message based on the identified service rule.

Some embodiments provide a novel method for configuring a set of service one or more nodes on a host to perform context-rich, attribute-based services on the host computer, which executes several data compute nodes (DCNs) in addition to the set of service nodes. The method uses a context-filtering node on the host to collect a first set of attributes associated with service rules processed by the set of service nodes on the host computer. The context filter also collects a second set of attributes associated with at least one data message flow of a DCN (e.g., of a virtual machine (VM) or container) executing on the host. After collecting the first and second sets of attributes, the context filtering node on the host compares the first and second sets of attributes to generate a service tag to represent a subset of the first set of attributes associated with the data message flow. The method associates this service tag with the data message flow. This service tag can then be used to identify the subset of attributes associated with the data message flow when a service node needs to process its attribute-based service rules for the data message flow.

The invention discloses an ReLU convolutional neutral network-based image denoising method. The method comprises the following steps of building an ReLU convolutional neutral network model, wherein the ReLU convolutional neutral network model comprises a plurality of convolutional layers and active layers after the convolutional layers, wherein the active layers are ReLU functions; selecting a training set, and setting training parameters of the ReLU convolutional neutral network model; training the ReLU convolutional neutral network model by taking a minimized loss function as a target according to the ReLU convolutional neutral network model and the training parameters of the ReLU convolutional neutral network model to form an image denoising neural network model; and inputting a to-be-processed image to the image denoising neural network model, and outputting a denoised image. According to the ReLU convolutional neutral network-based image denoising method disclosed by the invention, the learning ability of the neural network is greatly enhanced, accurate mapping from noisy images to clean images is established, and real-time denoising can be realized.

This work discloses a unicast, end-to-end network performance measurement process which is capable of determining internal network losses, delays, and probability mass functions for these characteristics. The process is based on using groups of closely-spaced communications packets to determine the information necessary for inferring the performance characteristics of communications links internal to the network. Computationally efficient estimation algorithms are provided.

A label applicator system provides for high speed, accurate label transfer from a web to items moving on an item transport along a path relative to the system. The items, such as bottles, have a contoured surface. The applicator includes a supply reel for supplying labels on a web and a take-up for taking up the web after transfer of the label. A drive roller moves the web through the applicator system. The system includes a web positioning assembly and a movable label applicator head. A contour sensor senses the bottle contour and develops a profile for the head to follow to apply the labels to the bottles. The supply, take-up and the drive are operably engaged with one another to maintain a relatively constant tension in the web. The web positioning assembly is configured to advance and retract the web to accommodate a pitch difference between the bottles in the bottle transport and the labels on the web and to accommodate movement of the decorating head toward and away from the bottles in the bottle transport.

In order for the feature extractors to operate with sufficient accuracy, a high degree of training is required. In this situation, a neural network implementing the feature extractor may be trained by providing it with images having known correspondence. A 3D model of a city may be utilized in order to train a neural network for location detection. 3D models are sophisticated and allow manipulation of viewer perspective and ambient features such as day/night sky variations, weather variations, and occlusion placement. Various manipulations may be executed in order to generate vast numbers of image pairs having known correspondence despite having variations. These image pairs with known correspondence may be utilized to train the neural network to be able to generate feature maps from query images and identify correspondence between query image feature maps and reference feature maps. This training can be accomplished without requiring the capture of real images with known correspondence. Capture of real images with known correspondence is cumbersome, time and resource-intensive, and difficult to manage.

Some embodiments provide a computer program for performing a color matching operation. The computer program identifies first and second images. Each image includes several pixels. Each pixel includes a hue component value. The computer program identifies a set of hue ranges for the first image based on analysis of the hue component values of pixels in the first image. The computer program identifies a set of hue ranges for the second image based on analysis of the hue component values of pixels in the second image. The computer program modifies pixel values of the first image to match pixel values of the second image based on the sets of hue ranges for the first and second images.

The Mobile Pulse System makes use of a client application which is installed in each mobile device of a customer to obtain dynamic measurements of the service that is provided to the mobile device by a wireless service provider. These client applications perform frequent tests to determine the level of service that they are presently receiving, which test results are transmitted to the Mobile Pulse System server for compilation and analysis. As a result of the number and diversity of these tests, the server can accurately map the level of service that is being provided by the wireless service provider to a customer. The server can portray the level of service as a function of the type of mobile device used by the customer, specific locations within the service area, time of day, type of communications, and other such relevant parameters.

The invention discloses a subject evaluation system and method based on a knowledge point system. The subject evaluation system and method based on a knowledge point system comprise a database module, a knowledge point selection module, a quiz evaluation module and a stage-passing grade module, wherein the database module comprises a quiz unit and a knowledge point unit; the quiz unit comprises a quiz sub unit, a quiz analysis sub unit and a quiz difficulty level sub unit, and is used for selecting questions for a test and automatically judging the test performance when a student submits the questions; each test question of the quiz sub unit is related with one or more knowledge points in the knowledge point unit; the knowledge point selection unit comprises a chapter selection unit, a blind test, a difficulty selection unit and a quiz generation unit; and the quiz evaluation module is used for evaluating the test paper completed by the student and the situation about mastering of knowledge points. The subject evaluation system and method based on a knowledge point system forms an objective and reasonable evaluation reference for learning and mastering of knowledge points for students, and provides an accurate basis for 'what to practice' for students so as to comprehensively improve the learning efficiency.

An approach is provided for generating a high dynamic range image from a low dynamic range image. The generation is performed using a mapping relating input data in the form of input sets of image spatial positions and a combination of color coordinates of low dynamic range pixel values associated with the image spatial positions to output data in the form of high dynamic range pixel values. The mapping is generated from a reference low dynamic range image and a corresponding reference high dynamic range image. Thus, a mapping from the low dynamic range image to a high dynamic range image is generated on the basis of corresponding reference images. The approach may be used for prediction of high dynamic range images from low dynamic range images in an encoder and decoder. A residual image may be generated and used to provide improved high dynamic range image quality.