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31 results about "Transformation operator" patented technology

Quick sparse Radon transformation method based on iterative shrinkage

The invention discloses a quick sparse Radon transformation method based on iterative shrinkage. The quick sparse Radon transformation method comprises the following steps: firstly, setting an initial variable value; secondly, constructing a transformation operator L and calculating generalized inverse (LTL)-1LT of the transformation operator L; thirdly, treating a seismic channel set d to be treated by utilizing the generalized inverse (LTL)-1LT of the transformation operator L; and lastly, judging if all channel sets in a seismic data cube are treated, if not, continuing to treat the seismic channel set d to be treated by utilizing the generalized inverse (LTL)-1LT of the transformation operator L, and if so, ending. According to the quick sparse Radon transformation method, for one seismic data cube collected by adopting the same collection parameters, the generalized inverse of the transformation operator L only needs to be calculated once, then the transformation operator L and the generalized inverse (LTL)-1LT of the transformation operator L are applied to all seismic channel sets, thereby greatly reducing calculated amount; and the iterative shrinkage algorithm only includes product operation of simple matrixes and vectors and threshold operation, greatly reduces the calculated amount relative to the conventional sparse Radon transformation, and better adapts to treatment of practical seismic data.
Owner:TSINGHUA UNIV

Super-resolution image processing

A method for iterative derivation of a master image from sampled images of non-identical, at least partially overlapping, regions of a scene. The method includes defining a transformation operator mapping positions within the master image to corresponding positions in the sampled image; a distortion operator simulating a modulation transfer function associated with an imaging sensor from which the sampled image was generated; and a sampling operator for reducing an image from the output resolution to the resolution of the sampled image. For each sampled image the transformation operator, distortion operator and sampling operator are applied to a current master image hypothesis to generate a predicted image A difference image is calculated which has pixel values corresponding to the difference in corresponding pixel values between the sampled image and the predicted image. A back-projection of each of the difference images is performed to generate a correction image for the current master image hypothesis. Finally, the correction images are employed to perform a correction to the current master image hypothesis to generate a new master image hypothesis. The correction to the current master image hypothesis includes combining the correction images by deriving a weighted average of values of corresponding pixels in the correction images. The weight of each pixel in each correction image is calculated as a function of a distance as measured in the sampled image between: a point in the sampled image to which the pixel in the correction image is mapped by the transformation operator, and at least one pixel centroid proximal to that point.
Owner:RAFAEL ADVANCED DEFENSE SYSTEMS

Website error-reporting screenshot classification method based on feature fusion

The invention discloses a website error-reporting screenshot classification method based on feature fusion. The method comprises the following steps: firstly, carrying out data enhancement on an imagedata set of error-reporting screenshots; zooming the image data to a uniform size, and randomly dividing the image data into a training set, a verification set and a test set; performing feature extraction on the image by using a part of network layer of the VGG16 convolutional neural network; extracting features of the image by using a scale-invariant feature transformation operator; fusing thetwo features through feature splicing to serve as final features of the image; and enabling the final features of the image to pass through a full connection layer, a Dropout layer and a Softmax layerto realize correct classification of error-reporting screenshots. According to the invention, machine learning is used to train the neural network for image classification, the workload of customer service staff is reduced, and the enterprise operation efficiency is improved; the data set is expanded by performing data enhancement on the data set image, so that the training is more sufficient; and the two image features are fused to obtain better classification accuracy.
Owner:浙江网新数字技术有限公司

Super-resolution image processing

A method for iterative derivation of a master image from sampled images of non-identical, at least partially overlapping, regions of a scene. The method includes defining a transformation operator mapping positions within the master image to corresponding positions in the sampled image; a distortion operator simulating a modulation transfer function associated with an imaging sensor from which the sampled image was generated; and a sampling operator for reducing an image from the output resolution to the resolution of the sampled image. For each sampled image the transformation operator, distortion operator and sampling operator are applied to a current master image hypothesis to generate a predicted image A difference image is calculated which has pixel values corresponding to the difference in corresponding pixel values between the sampled image and the predicted image. A back-projection of each of the difference images is performed to generate a correction image for the current master image hypothesis. Finally, the correction images are employed to perform a correction to the current master image hypothesis to generate a new master image hypothesis. The correction to the current master image hypothesis includes combining the correction images by deriving a weighted average of values of corresponding pixels in the correction images. The weight of each pixel in each correction image is calculated as a function of a distance as measured in the sampled image between: a point in the sampled image to which the pixel in the correction image is mapped by the transformation operator, and at least one pixel centroid proximal to that point.
Owner:RAFAEL ADVANCED DEFENSE SYSTEMS

Quick sparse Radon transformation method based on iterative shrinkage

The invention discloses a quick sparse Radon transformation method based on iterative shrinkage. The quick sparse Radon transformation method comprises the following steps: firstly, setting an initial variable value; secondly, constructing a transformation operator L and calculating generalized inverse (LTL)-1LT of the transformation operator L; thirdly, treating a seismic channel set d to be treated by utilizing the generalized inverse (LTL)-1LT of the transformation operator L; and lastly, judging if all channel sets in a seismic data cube are treated, if not, continuing to treat the seismic channel set d to be treated by utilizing the generalized inverse (LTL)-1LT of the transformation operator L, and if so, ending. According to the quick sparse Radon transformation method, for one seismic data cube collected by adopting the same collection parameters, the generalized inverse of the transformation operator L only needs to be calculated once, then the transformation operator L and the generalized inverse (LTL)-1LT of the transformation operator L are applied to all seismic channel sets, thereby greatly reducing calculated amount; and the iterative shrinkage algorithm only includes product operation of simple matrixes and vectors and threshold operation, greatly reduces the calculated amount relative to the conventional sparse Radon transformation, and better adapts to treatment of practical seismic data.
Owner:TSINGHUA UNIV

Method for revising terminal configuration, network side management unit, terminal and system

The invention discloses a method for restricting configuration modification and software upgrade of terminal equipment, which is applied to a network side management unit and terminal equipment, including: the management unit acquires terminal identification information; the management unit automatically generates a password according to the identification information , the password is calculated and generated according to the encryption algorithm and the identification information; the management unit initiates a login request to the terminal device, and sends the password to the terminal device; the terminal device receives the login request and the password; the terminal device calculates and verifies the correctness of the password, and if the verification is passed, the terminal device grants the login user the authority to modify the configuration and upgrade the software of the terminal device. The invention also discloses a system for realizing the method of the invention. The present invention can effectively restrict configuration modification and software upgrade of terminal equipment, and improve security; it can be used to prevent equipment from switching networks, reduce loss of operator assets, simplify operator terminal configuration and upgrade, and facilitate network expansion and transformation .
Owner:HUAWEI TECH CO LTD

ITRF conversion method based on conformal geometric algebra

The invention discloses an ITRF conversion method based on conformal geometric algebra. The ITRF conversion method comprises the following steps: 1, obtaining a to-be-converted station and coordinates of the to-be-converted station in an Euclidean space E3; 2, introducing a reference origin e0 and an infinite point e-infinity based on a covariant view angle, and converting the coordinates of the to-be-converted station point in an Euclidean space E3 into the coordinates of the to-be-converted station point in a conformal space; 3, in the conformal space, constructing a rotation operator, a translation operator and a scaling operator which have the same effect as rotation, translation and scaling in the Euclidean space E3; 4, according to the conversion type of the reference frame and the rotation operator, the translation operator and the scaling operator constructed in the step 3, converting the coordinates of the to-be-converted station point in the conformal space from any reference frame state at any moment to another reference frame state. According to the method, on the basis of unified operator expression, the conversion operator is directly calculated according to the conversion parameters, and then conversion is directly carried out, so complex matrix conversion is avoided, and a tedious conversion form and a complex calculation process are simplified.
Owner:NANJING NORMAL UNIVERSITY
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