An information processing apparatus performing processing for protecting privacy and security on an image uploaded to an SNS site is provided. The information processing apparatus includes: a region estimating unit configured to estimate candidate regions of object detection from an image; a topic estimating unit configured to estimate a topic of the image on the basis of text information accompanying the image; a region evaluating unit configured to evaluate the candidate regions estimated by the region estimating unit on the basis of relationships with the topic estimated by the topic estimating unit; and an image generating unit configured to generate an image on the basis of evaluation results acquired by the region evaluating unit. The topic estimating unit described above estimates the topic on the basis of words to which tags are added.

A method, computer system, and a computer program product for analyzing visual defects is provided. The present invention may include generating a template image. The present invention may include capturing a test image. The present invention may include performing an image registration between the template image and the test image. The present invention may include generating a registered test image. The present invention may include performing an image difference analysis between the registered test image and the template image. The present invention may include generating a differential image. The present invention may include synthesizing the registered, differential image, and template image. The present invention may include generating a synthetic image. The present invention may include inputting the synthetic image into a multi-scale detection network. The present invention may include generating a defect map.

The described technology is a technique related to an indoor localization method using deep learning. The indoor localization method comprises: opening a 3D tour comprising a plurality of panoramic images; receiving a first perspective image captured by a camera provided in the user device; calculating global features for the first perspective image and each of the plurality of panoramic images included in the 3D tour; selecting a most similar panoramic image to the first perspective image by using the calculated global features; computing an indoor location corresponding to a location of the camera on the 3D tour by using feature points included in the selected panoramic image and the first perspective image; and providing the computed indoor location to the user device.

Embodiments of the present disclosure provide methods, apparatus, systems, and computer program products for using an image of an integrated circuit (IC) including a plurality of cells to locate one or more target cells within the IC. Accordingly, in various embodiments, a footprint for each cell of the plurality of cells is encoded to transform the image of the IC into a two-dimensional string matrix. A string search algorithm is then applied on each encoded dopant region found in the two-dimensional string matrix using an encoded target layout cell to identify one or more candidate regions of interest within the image. Finally, a mask window is slid over each candidate region of interest while performing matching using match criteria to identify any target cells in the one or more target cells that are located within the candidate region of interest.

A method for risk based processing, the method may include detecting, based on first sensed information sensed at a first period, a suspected risk within an environment of a vehicle; selecting, from reference information, a situation related subset of the reference information, wherein the situation related subset of the reference information is related to the situation; selecting, from reference information, a suspected risk related subset reference information, wherein the potential risk related subset of the reference information is related to the potential risk; and determining whether the suspected risk is an actual risk, based at least on part on the suspected risk related subset reference information.

Disclosed are a method and a system for enhancing sound and picture quality based on scene recognition, and a display. The method includes: recognizing a real scene reflected in a current screen of the display; calculating sound and picture quality enhancement parameters matching the real scene; and controlling the display to play sound and picture corresponding to the real scene according to best sound and picture quality corresponding to the sound and picture quality enhancement parameters.

An embodiment of the present disclosure provides a method of providing a User Interface for serial images analysis in a user equipment, the method including: displaying a first cross-sectional image, a second cross-sectional image, and a third cross-sectional image on a first area of the user interface, which are related to a first image; displaying candidate nodule information related to the first image on at least one of the first cross-sectional image, the second cross-sectional image, and the third cross-sectional image; determining the candidate nodule information related to a user input as first nodule information related to the first image, based on the user input on the user interface; and displaying the first nodule information in such a way that the candidate nodule information related to the user input is replaced with the first nodule information, in which the candidate nodule information may be generated based on a first nodule dataset obtained by inputting the first image to a deep learning algorithm in a server.

There is provided a multi-scale object detection device. The device includes an image frame acquisition unit for acquiring a plurality of consecutive image frames, a critical region extractor for extracting at least one second critical region from a current image frame based on at least one first critical region extracted from a previous image frame among the consecutive image frames, a multi-scale object detector whose operation involves a first object detection process for the current image frame and a second object detection process for the at least one second critical region, and an object detection integration unit for integrating the results of the first and second object detection processes.

A system for reducing a search area for identifying correspondences identifies an overlap region within a first match frame captured by a match camera. The overlap region includes one or more points of the first match frame that are associated with one or more same portions of an environment as one or more corresponding points of a first reference frame captured by a reference camera. The system obtains a second reference frame captured by the reference camera and a second match frame captured by the match camera. The system identifies a reference camera transformation matrix, and/or a match camera transformation matrix. The system defines a search area within the second match frame based on the overlap region and the reference camera transformation matrix and/or the match camera transformation matrix.

A texture image compensation method, a texture detection method and a device, and an electronic device are provided. The texture detection method includes: performing an image difference calculation on a first texture image acquired by a texture detection device and a foreign object correction image acquired by the texture detection device to compensate foreign object information in the first texture image, and to acquire a second texture image; performing and the texture detection by using the second texture image.