Abstract: Systems and methods for image classification are disclosed. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, of selecting a predetermined number of training images that are representative of images associable with a particular topic category. One embodiment can include, extracting training image features from the training images, generating a set of descriptors characteristic of images associable with the particular topic category, and generating the particular set of predetermined models that correspond to the particular topic category based on the set of descriptors.

Abstract: Systems and methods for advertisement delivery optimization are disclosed. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, of identifying multimedia content associated with a web-user. One embodiment can include, analyzing the multimedia content to retrieve a set of descriptors, comparing the set of descriptors with metadata of a plurality of advertisements, selecting a candidate pool of advertisements from the plurality of advertisements based on relevancy indicated by the comparison, and presenting at least a portion of the candidate pool of advertisements to the web-user.

Abstract: Systems and methods for providing advertisement optimization services are disclosed. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, of analyzing a first set of images hosted by the web-publisher for display on the website. One embodiment can include, analyzing metadata associated with a set of advertisements available to the web-publisher for placement on the website, and identifying an advertisement suitable for placement on a webpage of the website for a fee.

Abstract: Systems and methods for image classification are disclosed. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, of selecting a predetermined number of training images that are representative of images associable with a particular topic category. One embodiment can include, extracting training image features from the training images, generating a set of descriptors characteristic of images associable with the particular topic category, and generating the particular set of predetermined models that correspond to the particular topic category based on the set of descriptors.

Abstract: A new approach contemplating a variety of improved methods and systems to perform intelligent image resizing on an image is proposed. The approach enables a user to interactively mark or select portions of the image to preserve and/or remove. An energy function can then be used to calculate values of an energy metric, for a non-limiting example, entropy, on every pixel over the entire image. Such calculated values can then be used to determine the optimal regions where new pixels are to be inserted or existing pixels are to be removed in order to minimize the amount of energy lost (for shrinking) or added (for growing) in the image.