The method and system may be used to provide an indication of a color value for a particular siding sample and to color match a specific siding product to the color value of the siding sample. The system receives a digital image of a siding sample and a desired color value to be matched. A color query module plots this desired color value as a desired color point in a multidimensional color space together with a plurality of color reference points. Each color reference point represents the color value of an existing siding product. The system determines a distance between the desired color point and each plotted color reference point within the color space and identifies the siding product associated with the color reference point that is located the shortest distance to the desired color point within the color space.

A wound assessment method which can estimate a moisture level of the wound, and related image capture device. The wound area is imaged at least twice where the wound is illuminated under different illumination light intensities. The first image captured using a relatively low illumination light intensity is analyzed to assess the wound, for example measuring its size, color and texture. The second image captures using a relatively high illumination light intensity (e.g. using a flash) is analyzed to estimate the moisture level of the wound. The moisture level estimation method extracts white connected components from the second image, and estimates the moisture level based on the number, sizes, and centroid distribution of the white connected components. A 3D image of the wound may also be captured, e.g. using a structured-light 3D scanner of the image capture device.

A method, a device and a terminal for generating training data is provided. The method for generating training data includes: obtaining an original image; determining a transferred image based on the image style transfer model and the original image, wherein the image style transfer model is obtained by minimizing a loss function, the loss function is determined by the original loss function the background loss function and the foreground loss function; determining the training data based on the transferred image. The difference between the generated training data and the target image is small, thereby improving the accuracy of the training model obtained by using the training data.

The invention discloses a method for determining a timestamp t of an image of a video stream V(t) comprising a plurality of images, said method comprising the steps of determining an acquired image descriptor of at least one of a plurality of acquired images Si of an acquired video stream during a display phase and determining a similarity level of an original image descriptor and the acquired image descriptor and if the similarity level of the original image descriptor and the acquired image descriptor fulfills at least one criterion, determining the timestamp t of the original image descriptor and assigning the timestamp t to the acquired image corresponding to the acquired image descriptor as an estimated timestamp T. Augmented information can be displayed to a user depending on the time stamp.

Systems and methods for applying an ensemble of segmentations to microscopy images of a tissue sample to determine if the tissue sample is representative of cancerous tissue. The ensemble of segmentations is applied to a plurality of greyscale or color microscopy images to generate a final image level segmentation and a final blob level segmentation. The final image level segmentation and final blob level segmentation are used to calculate a mean nuclear volume to determine if the tissue sample is representative of cancerous tissue.

An identity authentication method includes: obtaining first feature data of a first user image; performing quantization processing on the first feature data to obtain second feature data; and obtaining an identity authentication result based on the second feature data.

One embodiment is directed to a system for enabling two or more users to interact within a virtual world comprising virtual world data, comprising a computer network comprising one or more computing devices, the one or more computing devices comprising memory, processing circuitry, and software stored at least in part in the memory and executable by the processing circuitry to process at least a portion of the virtual world data; wherein at least a first portion of the virtual world data originates from a first user virtual world local to a first user, and wherein the computer network is operable to transmit the first portion to a user device for presentation to a second user, such that the second user may experience the first portion from the location of the second user, such that aspects of the first user virtual world are effectively passed to the second user.

Certain embodiments involve a model for enhancing text in electronic content. For example, a system obtains electronic content comprising input text and converts the electronic content into a grayscale image. The system also converts the grayscale image into a binary image using a grid-based grayscale-conversion filter, which can include: generating a grid of pixels on the grayscale image; determining a plurality of grid-pixel threshold values at intersection points in the grid of pixels; determining a plurality of estimated pixel threshold values based on the plurality of grid-pixel threshold values; and converting the grayscale image into the binary image using the plurality of grid-pixel threshold values and the plurality of estimated pixel threshold values. The system also generates an interpolated image based on the electronic content and the binary image. The interpolated image includes output text that is darker than the input text. The system can then output the interpolated image.

An image processing system includes: a receiving unit configured to receive an input of a plurality of image frames constituting a video from an imaging apparatus; a detection unit configured to detect a feature point included in an image frame to be processed in the plurality of image frames; and an output unit configured to output an output image obtained by superimposing an image frame to be processed of an area detected as a feature point on a background image generated from at least some of a plurality of image frames.

Methods and apparatus are disclosed for adjusting hyper-parameters of a neural network to compensate for noise, such as noise introduced via quantization of one or more parameters of the neural network. In some examples, the adjustment can include scaling the hyper-parameter based on at least one metric representing noise present in the neural network. The at least one metric can include a noise-to-signal ratio for weights of the neural network, such as edge weights and activation weights. In a quantized neural network, a learning rate hyper-parameter used to compute a gradient update for a layer during back propagation can be scaled based on the at least one metric. In some examples, the same scaled learning rate can be used when computing gradient updates for other layers.