Systems and methods disclosed for use in identifying and duplicating objects, particularly access devices such as house keys, office keys, automobile keys, and RFID key fobs. Within a singular housing, the customizable systems may include any or all of a key identification system, a key duplication system, an automobile key identification system, and/or an RFID key fob duplication system. Unique capabilities of the systems include the ability to verify that an existing automobile key matches data input by the user pertaining to the associated automobile. Further, the systems reduce frustration, error, and waste by programming a duplicate blank RFID key fob in a fully automated manner within the housing of the machine. To facilitate this process, blank RFID key fobs may be stored inside of the housing within RFID key fob containers that are readily stacked and dispensed.

Provided is a contour shape recognition method, including: sampling and extracting salient feature points of a contour of a shape sample; calculating a feature function of the shape sample at a semi-global scale by using three types of shape descriptors; dividing the scale with a single pixel as a spacing to acquire a shape feature function in a full-scale space; storing feature function values at various scales into a matrix to acquire three types of feature grayscale map representations of the shape sample in the full-scale space; synthesizing the three types of grayscale map representations of the shape sample, as three channels of RGB, into a color feature representation image; constructing a two-stream convolutional neural network by taking the shape sample and the feature representation image as inputs at the same time; and training the two-stream convolutional neural network, and inputting a test sample into a trained network model to achieve shape classification.

Example embodiments allow for training of encoders (e.g., artificial neural networks (ANNs)) to generate a color palette based on an input image. The color palette can then be used to generate, using the input image, a quantized, reduced color depth image that corresponds to the input image. Differences between a plurality of such input images and corresponding quantized images are used to train the encoder. Encoders trained in this manner are especially suited for generating color palettes used to convert images into different reduced color depth image file formats. Such an encoder also has benefits, with respect to memory use and computational time or cost, relative to the median-cut algorithm or other methods for producing reduced color depth color palettes for images.

A defect inspecting system includes a detector configured to image a sample and a host control device that acquires an inspection image including a defect and a plurality of reference images not including a defect site and generates a pseudo defect image by editing a predetermined reference image among the plurality of acquired reference images. An initial parameter is determined with which the pseudo defect site is detectable from the pseudo defect image. The host control device acquires a defect candidate site from the inspection image using the initial parameter, estimates a high-quality image from an image of a site corresponding to the defect candidate site using the parameter acquired in image quality enhancement, and specifies an actual defect site in the inspection image by executing defect discrimination. A parameter is determined with which a site close to the specified actual defect site is detectable using the inspection image.

The invention relates to the field of computer engineering for processing images that provides increased accuracy of finding and classifying a similar object . The technical result is achieved by: downloading files of a radiographic image which comprise metadata including information about the object or subject of the image and information about the image itself; encrypting the downloaded files if the above-mentioned files comprise personal data about a person; decrypting the above-mentioned, encrypted, downloaded files; and processing the radiographic image, wherein, as a result of the processing, the following occurs: finding and capturing a relevant region of the radiographic image; removing noise from the captured, relevant region of the radiographic image, wherein a region with a found object is meant by a relevant region of the radiographic image; compressing or unzipping a previously processed radiographic image; and finding a similar object in two previously processed images, and processing said object.

The present invention relates to an apparatus for task determination during brain activity analysis. The apparatus comprises an input unit (20), a processing unit (30), and an output unit (40). The input unit is configured to provide the processing unit with measurement data of the brain of a patient performing a task during brain activity analysis. The processing unit is configured to determine a measure of brain activity based on the measurement data of the brain. The processing unit is configured to determine: that the patient should perform a different task to the task they are currently performing and select the different task; or that the patient should continue performing the task that they are currently performing; or that the patient should stop performing the task; The determination comprises utilization of information relating to the task and the determined measure of brain activity and information relating to a plurality of reference tasks and associated plurality of reference measures of brain activity. The output unit is configured to output an indication that the patient should perform the different task, that the patient should continue performing the task, or that the patient should stop performing the task.

The present invention relates to an apparatus for task determination during brain activity analysis. The apparatus comprises an input unit (20), a processing unit (30), and an output unit (40). The input unit is configured to provide the processing unit with measurement data of the brain of a patient performing a task during brain activity analysis. The processing unit is configured to determine a measure of brain activity based on the measurement data of the brain. The processing unit is configured to determine: that the patient should perform a different task to the task they are currently performing and select the different task; or that the patient should continue performing the task that they are currently performing; or that the patient should stop performing the task; The determination comprises utilization of information relating to the task and the determined measure of brain activity and information relating to a plurality of reference tasks and associated plurality of reference measures of brain activity. The output unit is configured to output an indication that the patient should perform the different task, that the patient should continue performing the task, or that the patient should stop performing the task.

An image gaze correction method, apparatus, electronic device, computer-readable storage medium, and computer program product related to the field of artificial intelligence technologies are provided. The image gaze correction method includes: acquiring an eye image from an image; performing feature extraction processing on the eye image to obtain feature information of the eye image; performing, based on the feature information and a target gaze direction, gaze correction processing on the eye image to obtain an initially corrected eye image and an eye contour mask; performing, by using the eye contour mask, adjustment processing on the initially corrected eye image to obtain a corrected eye image; and generating a gaze corrected image based on the corrected eye image.

Embodiments of this application disclose a virtual scene display method performed by a computer device, which relate to the field of virtual scene technologies. The method includes: generating a virtual scene interface, the virtual scene interface including a scene image of a virtual scene captured by a virtual camera; displaying, in the virtual scene interface, a first scene image of one or more virtual objects in the virtual scene captured by the virtual camera using a first representation, the first representation being one of a 2D representation and a 3D representation; and in response to receiving a zoom operation on the virtual scene, displaying, in the virtual scene interface, a second scene image of the one or more virtual objects in the virtual scene captured by the virtual camera using a second representation, the second representation being the other one of the 2D representation and the 3D representation.

An information processing device according to the present invention includes: a memory; and at least one processor coupled to the memory. The processor performs operations. The operations includes: selecting a base image from a base data set that is a set of images including a target region that includes an object that is a target of machine learning and a background region that does not include an object that is a target of the machine learning; generating a processing target image that is a duplicate of the selected base image; selecting the target region included in another image included in the base data set; synthesizing an image of the selected target region with the processing target image; and generating a data set that is a set of the processing target images in which a predetermined number of the target regions are synthesized.