85 results about "Shadow mask" patented technology

The present disclosure relates to systems, methods, and non-transitory computer-readable media that detects shadows, removes shadows, and synthesizes shadows in a joint-framework. In particular, the disclosed systems access an object mask of an object and a digital image depicting the object and a shadow of the object. Furthermore, the disclosed systems perform object-centered shadow detection and removal to generate a modified digital image without the shadow by utilizing a shadow analyzer model. Moreover, the disclosed systems receive a user interaction to manipulate an object and generate a modified shadow utilizing a shadow synthesis model where the shadow synthesis model is conditioned on a shadow mask generated by the shadow analyzer model.

The invention relates to an interventional therapy target accurate positioning method and system based on an ultrasonic image. According to the method, a binary mask is generated by extracting an acoustic shadow area in an ultrasonic image, contrast enhancement parameters of different areas are dynamically adjusted based on the binary mask, and target spot edge details are enhanced while shadow area noise is suppressed; a shadow mask attention mechanism is combined to guide a neural network to accurately segment a target point probability graph, a segmentation boundary is evolved and optimized by integrating a level set constrained by a shadow region shape, and local smooth compensation is performed on registration deviation of a three-dimensional reconstruction model and a preoperative image by using a shadow perception deformation field correction strategy; and finally generating a puncture path for avoiding the dangerous structure. The problems of fuzzy target boundary, segmentation error accumulation and deformation compensation misalignment of a traditional method under acoustic shadow interference are effectively solved, and the pertinence of image enhancement, the accuracy of target positioning and the safety of an intervention path are remarkably improved.

The invention discloses a remote sensing image water body and shadow classification method based on a double-classification attention network, and relates to the technical field of remote sensing image analysis and geographic information processing, and the method comprises the steps: carrying out the preprocessing of a Sentinel-2 original image, and generating a multiband synthetic image with a predetermined resolution; calculating a normalized water body index and extracting a brightness channel, respectively generating a water body mask and a shadow mask, constructing a sample set, and dividing the sample set into a training set and a verification set; constructing a double-classification attention network model based on the training set, and performing optimization training on the model; and performing sliding window reasoning on the multiband synthetic image by adopting the trained double-classification attention network model, performing fusion splicing on the predicted binary masks, and outputting a double-band water body / shadow binary mask image. According to the method, a large amount of manual marking work needed by a traditional method is remarkably saved, interference of an ice and snow shadow area on a water body recognition result can be effectively overcome, and better robustness and stability are shown.

The invention provides a soft shadow image rendering method and device, electronic equipment, a computer readable storage medium and a computer program product, and the method comprises the steps: obtaining a to-be-rendered image which comprises a shadow region; generating a shadow mask corresponding to the to-be-rendered image based on the shadow area in the to-be-rendered image; obtaining point cloud data corresponding to the to-be-rendered image, and generating a soft shadow mask corresponding to the to-be-rendered image based on the point cloud data and the shadow mask; and performing image rendering on the to-be-rendered image based on the soft shadow mask to obtain a soft shadow image corresponding to the to-be-rendered image. Therefore, the rendering efficiency and the rendering effect of the soft shadow image can be improved.

Provided in the present application are a soft shadow image rendering method and apparatus, and an electronic device, a computer-readable storage medium and a computer program product. The method comprises: acquiring an image to be rendered that comprises a shadow area; on the basis of the shadow area in said image, generating a shadow mask for said image; acquiring point cloud data of said image, and on the basis of the point cloud data and the shadow mask, generating a soft shadow mask for said image; and on the basis of the soft shadow mask, performing image rendering on said image to obtain a soft shadow image of said image.

The invention discloses a fan height measuring method and device based on a high-resolution satellite image shadow. The method comprises the following steps: extracting a fan shadow by using a shadow extraction model based on a high-resolution satellite image containing a fan; the method comprises the following steps of: segmenting and removing a shadow mask of a fan blade by combining solar azimuth information with a straight line-by-line scanning method, and retaining a shadow mask of a fan tower; and calculating the shadow length of the fan tower according to the shadow mask of the fan tower, and calculating the fan height according to the shadow length of the fan tower. According to the invention, the fan height information can be rapidly obtained in a large range, the fan height can be accurately measured and calculated, and manpower and cost can be saved.

The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing to remove a shadow for an object. For instance, in one or more embodiments, the disclosed systems receive a digital image depicting a scene. The disclosed systems access a shadow mask of the shadow in a first location. Further, the disclosed systems generate the modified digital image without the shadow by generating a fill for the first location that preserves a visible location of the first location. Moreover, the disclosed systems generate the digital image without the shadow for the object by combining the fill with the digital image.

The application discloses a shadow removal method and device for remote sensing images based on detail enhancement and edge reconstruction. The method comprises the following steps: obtaining a remote sensing image training set, performing shadow detection on the shadow image to obtain an original shadow mask, performing morphological operation on the original shadow mask to obtain a divided shadow mask and a half-shadow-free image; inputting the divided shadow mask and the half-shadow-free image into a remote sensing image removal model to obtain a shadow removal result, constructing a hybrid loss function based on the shadow removal result and a real shadow-free image, and training the remote sensing image removal model based on the hybrid loss function; obtaining a to-be-detected remote sensing image, inputting the to-be-detected remote sensing image into the trained remote sensing image removal model after performing shadow detection on the to-be-detected remote sensing image, and obtaining a shadow-removed remote sensing image. The application can improve the quality of shadow removal of remote sensing images, has obvious advantages in overall image color recovery quality, shadow area micro detail structure recovery and edge pseudo mark processing.

The disclosure relates to a method of manufacturing a shadow mask (1) for stencil lithography The method comprises providing (S0) a blank multi-layer stack (1000); creating (S1) a first recess (22) that protrudes in a first direction (Z-) through a first thin-film layer (110) and into at least part of a support layer (120); depositing (S2) a metal layer (140) on a second thin-film layer (130) and depositing a resist layer (150) on the metal layer (140); creating (S3) a second recess (24a) that protrudes through the resist layer (150) in a second direction (Z+) opposite to the first direction (Z-); extending (S4) the second recess (24a) to an extended second recess (24b) that protrudes further through the metal layer (140) and through the second thin-film layer (130) in the second direction (Z+); creating (S5) a pattern of apertures (26) through the second- film layer (130).

The present application relates to computer vision and three-dimensional reconstruction technical field, disclose a kind of based on image recognition's building decoration component three-dimensional modeling method, method includes the following steps: receiving near-axis active illumination image sequence, solving camera pose and equivalent point light source trajectory;Inverse projection two-dimensional foreground mask generates maximum base envelope grid;Combining brightness gradient and texture high-frequency edge tensor field removes false shadow, extract effective sweep shadow mask;Tracking shadow residual optical flow displacement and combining light source trajectory analysis absolute depth, generate local three-dimensional point cloud;Surface reconstruction is executed to point cloud and opening plugging constructs negative space primitive entity grid;Extract the Laplace curvature energy of interface to generate normal shrinkage constraint, control entity grid after shrinkage and envelope grid execute Boolean difference set operation output model.The present application extracts absolute depth in featureless recessed area, and eliminates the boundary interference and distortion of grid Boolean operation.

The application discloses a video shadow detection method and device based on a dynamic prompt memory network, which can process confused shadows with the help of a projected shadow object, can aggregate time information without accumulating errors, and comprises a dynamic prompt module and a prompt-based memory module; the dynamic prompt module converts semantic information provided by a visual base model DINOv2 into a shadow mask when direct encoding of a shadow is difficult, local prompting focuses on semantic conversion and identifies a shadow position based on semantic information, and global prompting identifies a shadow boundary based on color and texture information; the memory module is used for solving deformation and long-term time consistency problems, preventing error accumulation, using local prompting as a time matching agent, reducing memory usage, and minimizing dependence on historical shadow masks; and the method can improve detection performance in a complex scene and maintain time consistency of results during long-term detection.

This invention relates to the field of image sensing data processing and discloses a method for diagnosing the thermal environment of blue-green spaces in cold-region cities based on multispectral remote sensing. The method includes the following steps: acquiring multispectral remote sensing images, three-dimensional building elevations, and solar apparent shape parameters; calculating the illumination shading coefficient of blue-green space pixels to form a three-dimensional dynamic shadow mask; constructing a microscopic phase transition evolution operator using the sensitivity gradient of radiation intensity in different polarization directions and mid-infrared reflectivity; inputting the mask and operator into the thermal infrared radiation measurement equation to reconstruct the dynamic surface temperature; solving the surface energy balance equation based on the dynamic surface temperature, separating the latent heat storage of phase transition energy, and constructing a latent heat buffer index; and performing a comprehensive diagnosis of the thermal environment health based on this index. This invention effectively overcomes the temperature measurement errors caused by complex shading and phase state interweaving, accurately isolates the latent heat energy of phase transition, and achieves precise positioning and objective quantitative diagnosis of microclimate anomalies in cold-region cities.

The present disclosure relates to systems, methods, and non-transitory computer-readable media that detects shadows, removes shadows, and synthesizes shadows in a joint-framework. In particular, the disclosed systems access an object mask of an object and a digital image depicting the object and a shadow of the object. Furthermore, the disclosed systems perform object-centered shadow detection and removal to generate a modified digital image without the shadow by utilizing a shadow analyzer model. Moreover, the disclosed systems receive a user interaction to manipulate an object and generate a modified shadow utilizing a shadow synthesis model where the shadow synthesis model is conditioned on a shadow mask generated by the shadow analyzer model.

The application discloses a calcified plaque recognition method based on intravascular ultrasound images and a storage medium. The method comprises the following steps: acquiring an intravascular ultrasound image training sample set, labeling a calcified region and a rear shadow region; constructing a U-shaped encoding and decoding segmentation network; calculating a composite loss function, which comprises a shadow consistency loss term; dividing the image into a fan-shaped region, using a differentiable calcified region rear edge detection module to construct an expected shadow mask, and taking the gray scale distribution difference between the expected shadow region and the real shadow label as the loss to guide the network to learn the physical constraint that the rear of the calcified region should be accompanied by a shadow; and inputting a to-be-recognized image into the trained network to obtain a recognition result. The application effectively suppresses the false detection of non-calcified high-light regions, introduces a shadow physical constraint, and the trained segmentation network can distinguish the true calcification as a high-light + shadow form, thereby being distinguished from other high-light structures, significantly reducing the false positive rate, and improving the accuracy and robustness of calcified plaque recognition.

The disclosure discloses a multi-modal based reflectivity remote sensing time sequence reconstruction method, device, medium and equipment, the method comprises: acquiring original multispectral remote sensing image and corresponding cloud mask and original multi-modal remote sensing image, and carrying out shadow detection based on the cloud mask to obtain a cloud shadow mask; performing partial convolution operation on the cloud shadow mask and the original multispectral remote sensing image to obtain the time sequence characteristics of optical data; after preprocessing the original multi-modal remote sensing image, obtaining the improved dual-polarization radar vegetation index, then combining the two kinds of data to obtain comprehensive multi-modal time sequence data; performing trend decomposition on the comprehensive multi-modal time sequence data to extract trend characteristics; taking the cloud shadow mask, the original multispectral remote sensing image, the time sequence characteristics of optical data and the trend characteristics of the comprehensive multi-modal data as the input of the reconstruction network to obtain the multispectral reflectivity time sequence reconstruction image with multispectral correlation and time sequence dependence.

The invention relates to a shadow mask and an electronic device. The shadow mask includes a lower inorganic layer, a base layer disposed on the lower inorganic layer, a first upper inorganic layer disposed on the base layer, a second upper inorganic layer disposed on the first upper inorganic layer, and an alignment key disposed on the second upper inorganic layer and having a stacked structure of at least four layers, the low refractive index inorganic layers and the high refractive index inorganic layers are alternately stacked with each other in a thickness direction of the lower inorganic layer.

The invention discloses an adaptive shadow generation method based on planar projection guidance and depth perception diffusion, and belongs to the technical field of computer vision and image synthesis. The method comprises the following steps: in a first stage, generating a hard shadow mask of a foreground object under a virtual light source through physical projection calculation, and providing geometric position and shape priori; in the second stage, multi-modal conditions such as a hard shadow mask, a background depth image and a foreground and background fusion image and noise latent variables are uniformly coded into a Token sequence, the Token sequence is input into a Diffusion Transform model, detail rendering is carried out through a self-attention mechanism, and a composite image with a realistic shadow is output. According to the method, the problems of shadow geometric distortion, inconsistent illumination, insufficient texture fitting and the like in the prior art are solved through a mixed frame combining physical guidance and neural rendering.

The present disclosure provides a method for manufacturing an organic light-emitting device, the method including an organic light-emitting element forming step of forming a plurality of organic light-emitting elements on a substrate, a first sealing layer forming step of forming a first sealing layer covering the organic light-emitting elements and having a groove in a non-display region, and a second sealing layer forming step of forming a second sealing layer on the first sealing layer using a shadow mask, wherein the second sealing layer forming step is a step of forming the second sealing layer in a state where an edge portion constituting a periphery of an opening of the shadow mask is disposed so as to be located on the groove.

The invention relates to a deep learning cloud detection method fusing object-oriented dynamic threshold and feature enhancement, and belongs to the field of remote sensing image cloud detection. The method comprises the steps that original satellite remote sensing images are acquired, and a dynamic threshold method based on a triangulation method is adopted for each image to generate a mask threshold; according to the mask threshold, generating a high-confidence cloud mask, a low-confidence cloud mask and a shadow mask in the remote sensing image in combination with an improved ACCA algorithm; according to the generated mask, matching a cloud object and a shadow object in the image to obtain a cloud mask image; for a wrong mask in the cloud mask image, eliminating false detection through mask replacement; constructing all finally generated cloud mask images into a remote sensing image training data set, and training a texture feature enhanced deep learning cloud detection network model through the data set; the trained model is used for predicting cloud in a satellite remote sensing image. According to the invention, the accuracy of cloud detection in complex scenes such as snow mountains, desert saline-alkali soil and urban highlight earth surfaces can be improved.

Disclosed is a deposition apparatus which includes a first electrostatic chuck having an opening defined therein and including a plurality of first electrodes, a second electrostatic chuck that is disposed over the first electrostatic chuck and that includes a lower surface to which a substrate is attracted, and a shadow mask that is disposed between the first electrostatic chuck and the second electrostatic chuck and that includes a mask attracted to an upper surface of the first electrostatic chuck and a plurality of conductive patterns disposed on the mask. The plurality of conductive patterns overlap the plurality of first electrodes when viewed on a plane.

To provide a method for manufacturing an organic light-emitting device that is excellent in water resistance and that can have a narrow frame.SOLUTION: A method for manufacturing an organic light-emitting device includes: an organic light-emitting element forming step of forming a plurality of organic light-emitting elements 6 on a substrate 1; a first sealing layer forming step of forming a first sealing layer 7 covering the organic light-emitting elements 6 and having a groove 10a in a non-display region; and a second sealing layer forming step of forming a second sealing layer 8 on the first sealing layer 7 using a shadow mask 20. The second sealing layer forming step is a step of forming the second sealing layer 8 in a state where an edge portion constituting a periphery of an opening of the shadow mask 20 is disposed so as to be located on the groove 10a.SELECTED DRAWING: Figure 4

The invention discloses a lightweight interpretable image shadow removal model based on an image reconstruction theory, which adopts a three-stage progressive network, in a stage I, an original image and a corresponding shadow mask image are received as input, a degradation process of a shadow region is learned through a gradient descent module, and a reconstruction result is sent to a near-end mapping module; the near-end mapping module completes the shadow removal work of the first stage under the supervision of the shadow mask graph to obtain a shadow-free graph; the second stage is the same as the first stage, and only the shadow-free image in the first stage is used as input; and a third stage of receiving the shadow-free image and the shadow mask image from the second stage, sending the shadow-free image and the shadow mask image to a space detail retention module after passing through a gradient descent module, and introducing the original image containing the shadow and the corresponding shadow mask image by the space detail retention module to adjust image details so as to obtain a final shadow-removed image. According to the method, the shadow removal effect is improved while the model is ensured to have relatively good interpretability, and the model is subjected to lightweight design to adapt to more practical application scenes.

A system for depositing an evaporation material on a substrate is provided. The substrate has a central axis. The system includes an evaporation vacuum chamber, at least one nozzle assembly, and a shadow mask. The nozzle assembly has a plurality of point evaporation sources disposed adjacent to and spaced from the central axis of the substrate, whereby the nozzle assembly provides molecules of the evaporation material that reach the substrate at an incident angle of 5 degrees or less.

An apparatus for making a multi-layer capacitive device may include a deposition chamber and a conductive material source within the deposition chamber. The apparatus may also include a dielectric material source within the deposition chamber and a micro-electromechanical system (MEMS) deposition shadow mask within the deposition chamber. The apparatus may also include a controller outside the deposition chamber and configured to selectively operate the conductive material source and the dielectric material source and operate the MEMS deposition shadow mask adjacent a substrate within the deposition chamber to selectively deposit alternating conductive material and dielectric material layers onto the substrate to make the multi-layer capacitive device.

A semiconductor device includes: a transparent base member; a bottom grid electrode formed on the transparent base member; a light-emitting organic layer formed on the bottom grid electrode; and a top grid electrode formed on the light-emitting organic layer. At least one of the bottom grid electrode or the top grid electrode is a mesh-type electrode, and at least one of the bottom grid electrode or the top grid electrode includes a plurality of first portions having a first thickness and forming a grid point portion and a second portion having a second thickness smaller than the first thickness and connecting the first portions.

The application discloses a high-resolution satellite image urban area shadow-removed ARD production method and device, and belongs to the technical field of remote sensing image processing. The method comprises the following steps: firstly, screening out images covering urban areas; performing radiation calibration on high-resolution satellite images covering urban areas to obtain apparent radiance images; based on the apparent radiance images, performing preliminary shadow detection by using a pre-trained deep learning model; using a near-infrared band of an atmospheric-corrected ground reflectivity image, performing false detection elimination on the preliminary detection result by adaptive threshold segmentation to obtain a final shadow mask; performing histogram matching processing on the shadow area based on the shadow mask on the atmospheric-corrected ground reflectivity image to realize shadow removal; and finally, outputting the shadow-removed ARD product. The application significantly improves the shadow detection precision and the quantitative reliability of the ARD product, and is suitable for large-scale ARD production of high-resolution satellite images in urban areas.

A high spatial resolution remote sensing image shadow restoration method includes: inputting a remote sensing image containing three visible light bands; converting it to the HIS color space; calculating the normalized shadow index; performing image segmentation on the normalized shadow index, extracting and optimizing the shadow mask; identifying and numbering the shadow blocks in the shadow mask; creating an adaptive rectangular window W that covers all shadow pixels of a certain shadow block; performing linear regression analysis on the spectral values ​​of non-shadow pixels and shadow pixels in the window; and using the linear regression equation to restore shadows to all shadow blocks in all bands of the remote sensing image. This high spatial resolution remote sensing image shadow restoration method overcomes the shortcomings of a single statistical measure in accurately characterizing the spectral statistical characteristics between non-shadow and shadow areas, and fully considers the differences in background features in different shadow areas. The shadow restoration results have high fidelity and are simple, stable, reliable, and computationally efficient.

A coating device comprising a sample carrier, a source, shadow mask and coating driver. The source comprises a plurality of targets such as a first target and second target. The source is arranged to coat at least one sample housed in the sample carrier. The shadow mask is disposed in a line-of-sight between the sample carrier and source. The shadow mask is arranged such that the first target provides a first coating contribution. The shadow mask is further arranged such that the second target provides a second coating contribution. The second coating contribution is different to the first coating contribution. At least one of the first and second coating contributions is non-uniform in a first dimension of the sample. The coating driver is arranged to independently control the first coating contribution and second coating contribution such that a thickness gradient of the coating in the first direction is variable.

Provided are a fluorinated compound for patterning a metal or an electrode (cathode), an organic electronic element using the same, and an electronic device thereof, wherein by using the fluorinated compound as a material for patterning a metal or an electrode (cathode), it is possible to form a fine pattern of the electrode without using a shadow mask, since it is easy to manufacture a transparent display having high light transmittance, it is possible to more easily apply UDC.

A system, assembly and method of producing an integrated circuit is provided. A shadow mask is adhered to and aligned with a substrate. There is a shadow mask gasket interposed between the shadow mask and the substrate. A thin film material is deposited on the substrate, such as a silicon wafer, through the shadow mask and the shadow mask gasket. The thin film material that is deposited results in a thin film feature having a boundary with a vertical edge.