23 results about "Image converter" patented technology

The invention discloses a multi-view graph converter incremental learning method for identifying related diseases. The method comprises the steps of 1, heterogeneous network construction, 2, mask contrast learning, 3, graph converter feature extraction, 4, channel attention fusion, 5, depth matrix decomposition prediction and 6, incremental learning updating. According to the method, a heterogeneous network is constructed to integrate multi-source similarity data, mask contrast learning is utilized to generate multi-view embedding so as to reduce noise, node position information is coded by means of a graph converter, multi-view features are fused through a channel attention mechanism, disease association is further predicted through depth matrix decomposition, and the disease association prediction accuracy is improved. And an incremental learning strategy is designed to realize dynamic updating of new data, a new result is obtained under the condition that original input data and model retraining are not needed, and the method can adapt to the condition of explosive increase of the data.

A structure inspection system includes an image conversion device located in a far edge of the structure inspection system that is proximate to a physical structure, and a near edge processor located in a near edge of the structure inspection system that is remote from the physical structure. The image conversion device receives an image of the physical structure, and renders a real time 3D model of the physical structure based on the first images. The near edge processor is configured to provide a baseline 3D model of the physical structure to the image conversion device. The image conversion device further compares the first real time 3D model with the baseline 3D model, and provides an indication when the first real time 3D model deviates from the baseline 3D model.

A machine learning method according to this embodiment trains a recognizer using a composite image, acquires a labeled real image based on an image captured by a sensor, stores, when at least one of the results of the recognition when the labeled real image is input to the recognizer match the label, results of the recognition performed by the recognizer, performs machine learning using a data set group including a plurality of the data sets, a real image and a composite image forming a pair in each of the data sets, thereby generating an image transformer, generating a labeled real image as a result of the image transformer transforming the composite image into the real image, and trains the recognizer based on the labeled real image.

An image processing apparatus comprises a receiver (401) receiving an image comprising first pixel brightnesses encoded in accordance with a perceptually uniform Electrical to Optical Transfer Function, EOTF. A converter converts this to second pixel brightnesses encoded in accordance with an EOTF representing a logarithmic mapping from optical light values to the second pixel brightnesses and an image processor circuit (411) applies a brightness adjustment processing to the second pixel brightnesses. The converter (410) comprises a first converter (601, 605) generating intermediate pixel brightnesses applying a logarithm function to the first pixel brightnesses A second converter (603) generates intermediate pixel brightnesses by applying a second logarithm function to an output value of the perceptually uniform EOTF for the first pixel brightness divided by a divisor equal to the first pixel brightnesses raised to a power of an exponent having a value exceeding 1. A combiner generates the second pixel brightnesses by combining the intermediate pixel brightnesses.

1. The name of the design product: image instrument. 2. The use of the design product: the design product is used for image measuring instrument, mainly for measuring parts. 3. The design points of the design product: in shape. 4. The picture or photo that can best show the design points: perspective view 1.

Complementary metal-oxide-semiconductor (CMOS) image sensor, comprising: i) a bias junction consisting of a first semiconductor material type and electrically coupled to a voltage source to apply a reverse bias of opposite polarity to a polarity of the first semiconductor material type to the bias junction; ii) a pixel in a pixel array, comprising: a photosensitive element, a first well consisting of a second semiconductor material type, and a second well consisting of the first semiconductor material type, and active CMOS elements used for at least one of 1) reading and 2) resetting the image data acquired by the photosensitive element; and iii) an implanted, buried layer consisting of the second semiconductor material type, extending over a region representing the pixel array below the second well consisting of the first semiconductor material type;wherein the implanted, buried layer, which consists of the second semiconductor material type, is arranged to interact with the blocking bias applied by the voltage source to the bias junction to reduce a parasitic current path between the second well, which consists of the first semiconductor material type and is used by the active CMOS elements, and a substrate, resulting in more uniform pixel-to-pixel performance in an image sensor with two or more pixels.

A construction compliance system includes an image capture device located in a far edge of the construction compliance system that is proximate to a construction project, and a near edge processor located in a near edge of the construction compliance system that is remote from the construction project. The image conversion device receives an image of a construction status of a construction project, and renders a three-dimensional model of the construction status based on the image. The near edge processor receives a three-dimensional model of a construction plan of the construction project, compares the three-dimensional model of the construction status with the three-dimensional model of the construction plan to determine whether the construction status deviates from the construction plan, and provides an indication when the construction status deviates from the construction plan.

The application discloses a streak image converter tube specific wave band quantum efficiency improving method and a streak image converter tube, and belongs to the technical field of fusion diagnosis and high-energy physics ultrafast diagnosis. In view of the problem that the quantum efficiency of the existing S20 photocathode is low in the blue-green wave band and restricts the detection sensitivity of the streak camera, a medium-metal composite metasurface structure with a subwavelength periodic arrangement is prepared on a cathode incident window, the guided mode resonance effect is used to couple the incident light to a photoelectric emission layer efficiently, and the light absorption and photoelectric conversion efficiency in the target wave band are enhanced. The metasurface structure is composed of a hexagonal grid-shaped distribution circular hole array formed by etching in a silicon dioxide window and an aluminum oxide medium column filled in the hole, and the structure parameters are determined by strict electromagnetic simulation optimization. The quantum efficiency of the cathode adopting the metasurface structure is improved from 14.34% to 19.09% in the 480 nm wave band, the integral sensitivity is improved from 170 mu A / lm to 289 mu A / lm, and the sensitivity of the streak image converter tube in the specific diagnostic window is improved.

The present invention relates to a display apparatus and a method of driving the same. The display apparatus includes a pixel, an image converter that generates a second image by correcting a gray scale of a first logo in a first image of the pixel, and a data driver that provides a data signal corresponding to the second image to the pixel. The image converter detects the first logo based on a value and a saturation of the first image, generates first map data corresponding to the first logo, and specifies the pixel corresponding to the first logo based on the first map data.

The present application provides a method for generating patterns or images on pastries using an AI model, the method comprising at least the following steps: providing a UI module for user to input keywords and descriptions; using an AI-based image module to generate black and white vector images according to the input content; processing the 2D images into digital instructions through an image converter module; sending the digital instructions to a laser patterning module; and using the laser patterning module to apply the patterns to the surface of the cookies.

An image analysis device includes: an image converter configured to generate target image frames based on video image frames captured by a terminal device; a plurality of image analyzers respectively comprising a plurality of image analysis models, the plurality of image analyzers being configured to: generate a plurality of analysis results by analyzing the target image frames respectively using the plurality of image analysis models different from each other, and perform a respective independent analysis scheduling regardless of analysis execution states of other image analyzers; and a security state determiner configured to determine a security mode of the terminal device based on the plurality of analysis results.

Text-to-image transformers configured in one aspect to associate an input text token with the specific object, apply latent blending with attention to a combination of keys and values for the input text token and a background image upon which to add the object; and which in another aspect perform latent blending with attention to keys and values for the object to add, keys and values for the background, and keys and values for a text prompt.

The present application relates to the field of astronomical, space science and solar observation coronagraph instrument, especially relates to a kind of external mask type image stabilization coronagraph, it includes in turn: external mask, heat rejection mirror, objective lens group, field stop, field lens, Lyot diaphragm, image converter group and linear polarizer, it further includes: image stabilization device, the image stabilization device includes: image stabilization lens group, guide mirror and image stabilization lens adjusting mechanism, wherein, the image stabilization lens group is located between objective lens group and field stop;The guide mirror is set to the incident light path direction parallel to external mask outside external mask, for collecting solar azimuth and solar elevation angle optical signal, obtains solar pointing deviation signal;The image stabilization lens adjusting mechanism is based on solar pointing deviation signal, adjusts the pose of image stabilization lens group, to compensate solar pointing deviation.The present application combines high-precision imaging and image stabilization technology organically, significantly improves the observation performance of coronagraph, provides reliable technical support for the research of solar activity and coronal structure.

Described herein is a skin detection and prevention system comprising an image converter module for receiving a first photograph and converting the first photograph to one or more new photographs, an image analyzer module for analyzing the one or more new photographs to identify one or more damaged skin areas of the new photographs, and a scoring module for receiving the analyzed second photograph and generating a skin score based on the one or more types of skin damage and the severity present in the one or more new photographs.

The present disclosure relates to a machine learning method, a machine learning system, and a computer-readable medium. The machine learning method according to the present embodiment includes training an identifier using a synthetic image, obtaining a labeled actual image based on a captured image captured by a sensor, saving an identification result of the identifier in a case where at least a part of the identification result in a case where the labeled actual image is input to the identifier coincides with a label, generating an image converter by performing machine learning using a dataset group including a plurality of datasets in which an actual image and a synthetic image are paired, converting the synthetic image into the actual image by the image converter, generating a labeled actual image, and training the identifier based on the labeled actual image.

The utility model discloses a guitar capable of assisting in indicating press positions, which comprises a guitar structure, an indicating structure is fixedly mounted above the guitar structure, the guitar structure comprises a guitar body serving as a body, a placement groove is formed in the surface of the guitar body, a through hole communicated with the placement groove is formed in the lower part of the guitar body, and the through hole is communicated with the placement groove. The indicating structure comprises a single-chip microcomputer, an image converter, an image capturer, a wireless module and a lamp holder module are electrically embedded and installed on the surface of the single-chip microcomputer, the single-chip microcomputer is fixedly installed in a connecting frame, an electronic base is fixedly installed on one side in the connecting frame, and meanwhile the electronic base is electrically connected with the single-chip microcomputer. A button electron for providing a power source is installed in the electronic base in a clamped mode, a frame cover plate is rotatably installed on the upper portion of the surface of the connecting frame, and the guitar capable of assisting in indicating pressing positions can provide a working power source through the arranged button electron.

Augmented reality applications require precise camera calibration to reduce the overall target registration errors. The camera calibration determines the mathematical model of the camera in order to determine how the physical world space is mapped to the camera image space and thus is highly dependent on the optics of the camera. The camera calibration algorithm normally assumes that the optics of the camera is rigidly fixed, which in fact is not at least for tilted laparoscopic cameras as illustrated in FIGS. 6 to 8. Furthermore, any mechanical play between elements of the objective and the image converter will render the optics variable. According to the invention markers to will be placed within the field of view of the laparoscopic camera, which allows for determination of rotation of the optical part and mechanical misalignment without the necessity or providing any additional sensor.

Display driving apparatus and driving method. A display driving apparatus for improving sharpness of an image according to an aspect of the present invention includes a luminance calculator for calculating first luminance data corresponding to a first resolution and second luminance data corresponding to a second resolution smaller than the first resolution using input image data, an offset calculator for calculating an offset based on the first luminance data and the second luminance data, an input image converter for converting the input image data into input image data to which the calculated offset has been applied, a first data output unit for generating output image data for a first panel using the converted input image data and outputting the generated output image data, and a second data output unit for generating output luminance data for a second panel using the second luminance data and outputting the generated output luminance data.

An image conversion device includes an image capture device and a renderer. The image capture device captures a plurality of two-dimensional (2D) images. The renderer receives the 2D images and renders a 3D model of an object captured in the 2D images. In rendering the 3D model, the renderer first renders a binary edge map of the object, and next models textures for the 3D model.

The inventive method involves receiving as input a representation of an ordered set of two-dimensional images. The ordered set of two-dimensional images is analyzed to determine at least one first view of an object in at least two dimensions and at least one motion vector. The next step is analyzing the combination of the first view of the object in at least two dimensions, the motion vector, and the ordered set of two-dimensional images to determine at least a second view of the object; generating a three-dimensional representation of the ordered set of two-dimensional images on the basis of at least the first view of the object and the second view of the object. Finally, the method involves providing indicia of the three-dimensional representation as an output.

The invention discloses a traveling wave deflection miniaturized streak image converter tube, and belongs to the field of optical ultrafast imaging. The fluorescent lamp comprises various electrodes (a cathode, a grid electrode, a focusing electrode and an anode), a traveling wave deflector, a fluorescent screen and the like. The device is characterized in that the electrodes and the traveling wave deflectors are all made of good conductor metal materials. The spherical cathode can reduce the path difference of emitted electrons at different positions. The grid electrode and the focusing electrode are both of a short cylinder structure and connected with negative high voltage. The anode is of a conical cylinder structure, and the radius of the incident end of the electron beam is smaller than that of the emergent end of the electron beam. The traveling wave deflector comprises two metal sheets with periodic structures, the two metal sheets are not limited to be parallelly or symmetrically placed in the anode, and the traveling wave deflector is matched with electron beams with different energies by controlling main structural parameters of the traveling wave deflector, so that the traveling wave deflector and the electron beams are kept working synchronously in ultrafast time. Four ports of the two traveling wave deflectors are respectively connected with coaxial ports, and the impedance is not limited to 50 ohms. The traveling wave deflector has high deflection sensitivity, and the voltage of a scanning power supply is greatly reduced. The traveling wave deflection miniaturized streak image converter tube has the length of about 100 mm and the diameter of about 50 mm, and has the advantages of compact structure, light weight, energy conservation and the like.

An image masking system (100) is disclosed. The system (100) includes a segmentation module (130) configured to extract one or more regions of interest by processing an input query image using a segmentation network. The segmentation module (130) is further configured to select one or more segments from the one or more extracted regions of interest based on a user indicator. The system (100) includes a mask generation module (140) configured to generate a binary mask for the selected segments on the input query image. The system (100) further includes an image transformer module (150) configured to generate a masked image by performing an arithmetic operation on the binary mask and the input query image. The image transformer module (150) is further configured to extract an embedding of the masked image using one of a convolutional neural network architecture or a Transformer architecture.

An image processing device comprises a receiver (401) that receives an image comprising first pixel brightnesses encoded according to a perceptually uniform electro-optical transfer function (EOTF). A converter converts this into second pixel brightnesses encoded according to an EOTF that represents a logarithmic mapping of optical light values ​​to the second pixel brightnesses, and an image processor circuit (411) applies brightness adjustment processing to the second pixel brightnesses. The converter (410) comprises a first converter (601, 605) that generates inter-pixel brightnesses by applying a logarithmic function to the first pixel brightnesses.A second converter (603) generates inter-pixel brightnesses by applying a second logarithm function to an output value of the perceptually uniform EOTF for the first pixel brightness divided by a divisor equal to the first pixel brightness raised to a power with an exponent having a value greater than 1. A combiner generates the second pixel brightnesses by combining the inter-pixel brightnesses.