67 results about "Image converter" patented technology

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.

The invention provides a space-time resolution X-ray diagnosis system, relates to the technical field of X-ray diagnosis systems, aims to realize convenient cathode replacement, no circulating water leakage risk and imaging monitoring function, and relates to a pinhole / slit imaging system assembly and an air chamber type X-ray streak camera. The pinhole / slit imaging system assembly is mounted on a front panel of the air chamber type X-ray streak camera; the air chamber type X-ray streak camera comprises an air chamber and a camera assembly arranged in the air chamber. The camera assembly comprises an X-ray scanning image converter tube installed at the front end of the air chamber. A circulating water refrigerating system in the camera assembly is completely arranged in the air chamber; the pinhole / slit imaging system assembly is used for aiming at the position of a target spot and imaging X-rays emitted by the target spot to a cathode slit of the air chamber type X-ray streak camera, and the X-ray scanning image converter tube is used for achieving time scale light back illumination coupling. The method has the advantages of improving the use convenience and prolonging the service life of the device.

The invention provides a method for generating a pattern or an image on a cake by using an AI model, and the method at least comprises the following steps: providing a UI module for a user to input keywords and descriptions; generating an image of a black and white vector according to the input content by using an AI-based image module; processing the 2D image into a digital instruction through an image converter module; sending the digital instruction to a laser patterning module; and applying a pattern to the biscuit surface using a laser patterning module.

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 system implements self-supervised learning through contrastive learning using an image transformer. The transformer receives medical images for training an Artificial Intelligence (AI) model, and executes a first cropping and prediction operation by (i) cropping a first patch P from a first random location L from an image A selected from the plurality of medical images and (ii) training a classification head to predict that the first patch P is part of the image A. The transformer executes a second cropping and prediction operation by (iii) cropping a second patch P from a second random location L from the image A selected from the plurality of medical images and (iv) training the classification head to predict that the second patch P forms no part of an image B selected from the plurality of medical images. The transformer issues a determination that the image B is different than the image A.

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.

The ultrafiltration membrane comprises a transparent membrane cylinder, membrane wires, an end cover, a water inlet and a water outlet, the cylinder wall of the transparent membrane cylinder is further provided with a concentrated water outlet and a sludge discharge port, the membrane wires are arranged in the transparent membrane cylinder, a plurality of low-light perspective devices are arranged on a cylinder body of the transparent membrane cylinder in a staggered mode, the low-light perspective devices extend into the transparent membrane cylinder, and the end cover is arranged on the end cover. The low-light perspective device comprises a transparent shell, a cesium photocathode is arranged at the front end in the transparent shell, the cesium photocathode is connected with the near-infrared light image converter tube, and the tail end of the transparent shell is connected with a hole in the cylinder wall of the transparent film cylinder in an embedded mode. According to the utility model, the transparent membrane cylinder of the ultrafiltration membrane is visual and is assisted by the low-light perspective device, so that not only can the pollutant concentration and pollutant accumulation condition of the existing ultrafiltration system be directly visualized, but also the pollution degree of the membrane silk can be clearly known by using the low-light perspective device.

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.

The invention relates to a festival blessing device and a festival blessing method, which are characterized in that relatives and friends or guests write his / her wishes or festival blessings, selected gifts and his / her names in a writing column of a screen pull-down menu, and then confirm and upload the wishes or the wishes, the selected gifts and the names; a character and image recognizer in the background server automatically and sequentially displays characters and images in a middle display area in a queue mode, the characters and the images are gradually increased, and the characters and the images move forwards in a rolling mode, and meanwhile a character and image converter automatically converts the characters and the images into voice and synchronously broadcasts the voice along with moving of the scrolled characters and the scrolled images. And the lower display area is an alternative display area for personal introduction and blessing of the blessing person, or words or images of the blessing person, and is presented with the name of the blessing person in a rolling manner at the same time. The system has the advantages that: firstly, off-line blessing, wedding celebration or blessing is realized, and the dynamic property is strong, so that a blessing or blessing person can personally feel true blessing from relatives, friends and guests; and secondly, the festive atmosphere can be well increased, and the festive and uplift effects are achieved.

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.

An image convertor for visual inspection to convert images captured by two visual inspection devices, each of which comprises a main imaging unit that vertically captures images of an inspected object to be subjected to visual inspection, and a plurality of light sources installed between the main imaging unit and the inspected object comprises an image storage unit that stores a first image group and a second image group, a training data set generation unit that generates a pair of images in the first image group and corresponding images in the second image group as a training data set and an image conversion model learning unit that performs machine learning using the generated training data set to generate an image conversion model that converts an image in the first image group into the corresponding image in the second image group.

The invention discloses a traditional Chinese medicine diabetic retinopathy difference analysis system and method based on artificial intelligence, and relates to the technical field of artificial intelligence, and the system comprises a real-time adjustment end, a difference analysis end and a formula generation end; the real-time adjusting end is used for automatically generating retina image texture information of the diabetic patient through an image converter by detecting the retina texture of the diabetic patient in real time; the difference analysis end is used for receiving a retinal texture comparison result of a diabetic patient in real time; the formula generation end is used for receiving the retinopathy difference data in real time and taking standard traditional Chinese medicine formulas set by different lesions as the basis according to the retinopathy difference data. According to the traditional Chinese medicine diabetic retinopathy difference analysis system and method based on artificial intelligence, the retina comparison image is zoomed or expanded in real time according to the sizes of retinas of different patients, the accuracy of diabetic retina difference analysis is improved, and the accuracy of diabetic retina difference analysis is improved.

The invention provides bone age detection equipment and a bone age measurement method. The bone age detection equipment comprises a host, a detection base, an ultrasonic image transducer and a deformable water bag, the deformable water bag is arranged at an acoustic window opening of the ultrasonic image transducer, degassing water is arranged in the deformable water bag, and the ultrasonic image transducer is immersed in the degassing water; the host receives an operation instruction of an operator, controls the ultrasonic image transducer to acquire an ultrasonic image of a to-be-detected part according to the operation instruction, sequentially performs coarse positioning and fine positioning on the acquired ultrasonic image of the to-be-detected part, screens out a standard section ultrasonic image of the to-be-detected part, and transmits the standard section ultrasonic image to the ultrasonic image transducer; the bone maturity degree is calculated according to the standard section ultrasonic image of the to-be-measured part, the standard section ultrasonic image of the to-be-measured part can be rapidly and accurately positioned, dependence of manual operation is reduced, errors of the manual operation are avoided, and the speed and precision of ultrasonic bone age evaluation are improved.

An image convertor for visual inspection to convert images captured by two visual inspection devices, each of which comprises a main imaging unit that vertically captures images of an inspected object to be subjected to visual inspection, and a plurality of light sources installed between the main imaging unit and the inspected object comprises an image storage unit that stores a first image group and a second image group, a training data set generation unit that generates a pair of images in the first image group and corresponding images in the second image group as a training data set and an image conversion model learning unit that performs machine learning using the generated training data set to generate an image conversion model that converts an image in the first image group into the corresponding image in the second image group.

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.

An image processing apparatus includes a receiver (401) that receives an image including a first pixel brightness encoded according to a perceptually uniform electro-optical transfer function (EOTF). A converter converts this to a second pixel brightness encoded according to an EOTF representing a logarithmic mapping from an optical light value to the second pixel brightness, and an image processor circuit (411) applies a brightness adjustment process to the second pixel brightness. The converter (410) includes a first converter (601, 605) that generates an intermediate pixel brightness that applies a logarithmic function to the first pixel brightness. A second converter (603) generates an intermediate pixel brightness by applying a second logarithmic function to an output value of the perceptually uniform EOTF for the first pixel brightness divided by a divisor equal to an exponent of the first pixel brightness, the exponent having a value greater than 1. A combiner generates the second pixel brightness by combining the intermediate pixel brightness.

The present invention relates to the field of image conversion technology, and discloses a multi-view conversion method based on a multi-view consistency diffusion model. A multi-view consistency diffusion model is trained through a unified multi-view to multi-view conversion framework based on a diffusion model. The conversion framework has a new self-supervised training strategy, a consistency and adversarial supervision strategy, which utilizes the existing 2D single-view image converter and 3D Gaussian splash technology to generate pseudo-true values ​​as supervision signals, thereby enhancing view consistency and high-frequency details; the multi-view consistency diffusion model trained by the conversion framework also includes a latent multi-view consistency module, which utilizes the latent 3DGS module as the underlying 3D representation to promote information exchange across multiple views, thereby introducing 3D priors into the diffusion model to ensure view consistency. Finally, a joint optimization strategy is proposed, which can achieve a better trade-off between consistency and authenticity.

The present invention relates to a technology for performing low-light image data augmentation by converting a bright image such as a daytime situation into a low-light image such as a nighttime situation, and a low-light image data augmentation system according to an embodiment includes: a training data configuration unit for configuring training data on the basis of a first image generated in a first environment classified on the basis of illuminance and a second image generated in a second environment in low illumination compared to the first environment; an input image conversion unit for converting the first image into the second image and the second image into the first image, by receiving the first image and the second image as inputs; and a calculation unit for calculating a total loss for training a model by comparing an input image with at least one of the converted first image or the converted second image, wherein the input image conversion unit can convert the first image in the first environment into the second image in the second environment on the basis of a brightness degree (b) and a weight (w), through the model trained using the total loss.

To provide an image conversion device and method capable of converting still images into natural moving images, and a computer-readable recording medium.SOLUTION: An image conversion device that converts images using an artificial neural network includes: an image receiving unit that receives an image from a user; a template acquisition unit that acquires at least one image conversion template; and an image converter that converts a still image into a moving image using the at least one acquired image conversion template. The image converter includes a step of converting the still image received by the image receiving unit into the moving image.SELECTED DRAWING: Figure 1

The present invention belongs to the field of optoelectronic imaging technology. Aiming at the problem that the streak tube imaging lidar developed at present is difficult to meet the detection requirements of large field of view and high precision, a four-dimensional detection system for a large detection field of view and high-precision streak tube imaging lidar is provided, which includes a pulsed laser, a transmitting optical system, a delay system, a receiving optical system, a fiber optic image converter, a streak tube detector, a CCD camera and a signal processing system. Among them, the streak tube detector uses a large detection area streak tube with a single lens focusing system, realizing a large detection field of view and improving the range resolution in three directions. At the same time, it can image under the condition of the movement of the target object, meeting the requirements of large detection range and high-precision diagnosis.

A display device includes: a visual sensor for generating visual sensing data by sensing an eye of a user; a display panel including a display area and pixels disposed on the display area; an image converter for generating a second image signal by converting a first image signal of the pixels based on the visual sensing data; and a data driver for providing the pixels with data signals corresponding to the second image signal. The image converter generates visual information based on the visual sensing data, determines a first area and a second area different from the first area of the display area based on the visual information, and generates the second image signal by converting grayscales of the second area in the first image signal.

Vehicle camera monitoring system that includes the following: an electronic control unit (ECU) located in a vehicle equipped with the vehicle camera monitoring system, wherein the ECU comprises an electronic circuit and associated software; a support arm movably arranged on a side panel of the vehicle, wherein the support arm has a base end attached to the side panel and a distal end opposite the base end; wherein the support arm is pivotably attached to the side panel of the vehicle; a camera positioned at the distal end of the support arm; wherein the camera comprises a lens and an image sensor and wherein the image sensor comprises a two-dimensional image sensor array with at least one million photosensors arranged in rows and columns; wherein the support arm is movable between a stowed and an extended position; wherein the support arm is located in the stowed position at an opening on the side panel of the vehicle, wherein an outer surface of the support arm is coplanar with an outer surface of the side panel; wherein, when the support arm is in the stowed position and the outer surface of the support arm is coplanar with the outer surface of the side panel, the camera is positioned within the outer surface of the side panel; wherein the support arm is extended from the side panel in the extended position, so that the camera is positioned outside the side panel of the vehicle; a cover element that covers the opening on the side panel at least when the support arm is in the extended position; wherein the cover element is movable between a covering position, in which the cover element covers the opening, and a non-covering position, in which the cover element does not cover the opening; wherein the cover element is in the covering position when the support arm is extended, and wherein the cover element is in the non-covering position when the support arm is stowed; the camera captures image data when the support arm is extended and delivers the captured image data to the ECU; and wherein the captured image data are processed in the ECU for at least one of the group consisting of (i) the display of video images derived from the image data captured by the camera and provided to the ECU, and (ii) the detection of an object outside the vehicle that is within a field of view of the camera, and vehicle camera monitoring system comprising a front cover element arranged in front of a pivot axis of the support arm, wherein the front cover element is in a front cover position covering a front opening when the support arm is in the extended position and when the support arm is in the stowed position, and wherein the front cover element is moved from the front cover position to a non-covering position when the support arm is moved beyond the extended position in a direction opposite to the stowed position.

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.

Disclosed is a computing device, which includes a processor, a camera that captures RGB image data, a memory that stores image data including the RGB image data, and a pupil detection device that detects a pupil from the RGB image data stored in the memory in response to a request of the processor. The pupil detection device includes an image converter that receives the RGB image data, detects first eye area data including eye area information from the received RGB image data, and converts the first eye area data into second eye area data having IR (InfraRed) image characteristics by using a deep neural network, a pupil candidate detector that detects pupil candidate data from the second eye area data, and a pupil boundary detector that detects pupil boundary data from the pupil candidate data.

The invention relates to the technical field of streak cameras, and provides a streak camera coupling structure and a non-disassembly transportation protection method, and the streak camera coupling structure comprises a positioning sleeve which sleeves a CMOS camera and is fixedly connected with the CMOS camera, and the outer wall of the positioning sleeve is of a spherical structure; the positioning seat is provided with a ball hole matched with the outer wall of the positioning sleeve; the first bracket is used for supporting and fixing the scanning image converter tube; the second bracket is used for supporting the image intensifier and is provided with a through hole matched with the outer wall of the image intensifier; the leveling seat is fixed behind the CMOS camera; the at least three elastic components are arranged on the leveling seat and can provide elastic thrust for the rear end of the CMOS camera, the end parts, close to the CMOS camera, of the elastic components form a positioning plane, and the positioning plane is perpendicular to the axis of the scanning image converter tube; and the plurality of axial tightening pieces are in threaded connection with the leveling seat so as to be propped against the rear end of the CMOS camera after the streak camera is coupled. According to the invention, the input surface of the CMOS camera can be automatically leveled, and lossless and undetachable transportation can be conveniently realized.

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.