Methods and apparatus for using features of images representing content items to improve the presentation of the content items are disclosed. In one embodiment, a plurality of digital images are obtained, where each of the images represents a corresponding one of a plurality of content items. Image features of each of the digital images are determined. Additional features including at least one of user features pertaining to a user of a client device or contextual features pertaining to the client device are ascertained. At least a portion of the content items are provided via a network to the client device using features that include or are derived from both the image features of each of the plurality of digital images and the additional features.

According to exemplary methods of training a convolutional neural network, input images are received into a computerized device having an image processor. The image processor evaluates the input images using first convolutional layers. The number of first convolutional layers is based on a first size for the input images. Each layer of the first convolutional layers receives layer input signals comprising features of the input images and generates layer output signals that include signals from the input images and ones of the layer output signals from previous layers within the first convolutional layers. Responsive to an input image being a second size larger than the first size, additional convolutional layers are added to the convolutional neural network. The number of additional convolutional layers is based on the second size in relation to the first size. The additional convolutional layers are initialized using weights from the first convolutional layers. Feature maps comprising the layer output signals are created.

The image processing apparatus includes a calculator configured to calculate, using luminance values of one or more input images produced by photoelectric conversion of multiple polarized lights whose polarization angles are mutually different, an angle-dependent component at a specific polarization angle among angle-dependent components that are luminance components changing depending on the polarization angle. The apparatus further includes a producer configured to produce an output image using the angle-dependent component at the specific polarization angle.

A method of inspecting patterns to-be-inspected having regular intervals, the same widths and heights by using an image of the patterns to-be-inspected is disclosed. The method includes the steps of: obtaining centroids, widths and heights of the patterns to-be-inspected from an image of the patterns to-be-inspected; obtaining regular intervals, a mean of widths and a mean of heights of the patterns to-be-inspected, as information of design data, from the centroids, the widths and the heights; and inspecting the patterns to-be-inspected by using the information of the design data and edges of the image of the patterns to-be-inspected.

An image recognition apparatus is provided which comprises a first extracting means for extracting, from every registration image previously registered, a set of registration partial images of a predetermined size, and a second extracting means for extracting, from an input new image, a set of new partial images of a predetermined size. The apparatus further comprises a discriminating means for discriminating an attribute of the new partial image based on a rule formed by dividing the set of the registration partial images extracted by the first extracting means, and a collecting means for deriving a final recognition result of the new image by collecting discrimination results by the discriminating means at the time when the new partial images as elements of the set of the new partial images are input.

A technique and associated imaging system is provided that selectively acquires the myelin water signal by utilizing a multiple inversion RF pulses to suppress a range of long T.sub.1 components including those from axonal and extracellular water. This leaves the myelin water, which has been suggested to have short T.sub.1, as the primary source of the image. After long T.sub.1 suppression, the resulting image is dominated by short T.sub.2 in the range of the myelin water (T.sub.2*<20 ms at 3 T). This result confirms that the short T.sub.1 component has short T.sub.2* and, therefore, the resulting image is a myelin water image.

Systems and techniques for dynamically capturing and reconstructing lighting are provided. The systems and techniques may be based on a stream of images capturing the lighting within an environment as a scene is shot. Reconstructed lighting data may be used to illuminate a character in a computer-generated environment as the scene is shot. For example, a method may include receiving a stream of images representing lighting of a physical environment. The method may further include compressing the stream of images to reduce an amount of data used in reconstructing the lighting of the physical environment and may further include outputting the compressed stream of images for reconstructing the lighting of the physical environment using the compressed stream, the reconstructed lighting being used to render a computer-generated environment.

Methods and apparatuses for analyzing digital pathology images are provided. The methods and apparatuses may provide estimates of staining intensity and proportion score in regions of interest within an image. Digital pathology images may be scored according to these metrics. The methods and apparatuses disclosed herein utilize various predetermined thresholds, parameters, and models to increase efficiency and permit accurate estimation of characteristics of a stained tissue sample.

A method of identifying, with a camera, an object in an image of a scene, by determining the distinctiveness of each of a number of attributes of an object of interest, independent of the camera viewpoint, determining the detectability of each of the attributes based on the relative orientation of a candidate object in the image of the scene, determining a camera setting for viewing the candidate object based on the distinctiveness of an attribute, so as to increase the detectability of the attribute, and capturing an image of the candidate object with the camera setting to determine the confidence that the candidate object is the object of interest.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, to generate a scannable document. In one aspect, a method includes receiving a scan request, wherein the scan request includes a plurality of text images; for each text image of the plurality of text images: rectifying the text image to generate a text image with parallel image lines, generating a plurality of word bounding boxes that enclose one or more connected components in the text image, wherein each word bounding box is associated with a respective word, and generating, for each respective word in the text image, a plurality of points that represent the respective word; combining the plurality of text images to form a single text document; and providing the combined image as a scannable document.