50results about How to "Effectively delete" patented technology

The invention discloses a method for automatically matching multisource space-borne SAR (Synthetic Aperture Radar) images based on an RFM (Rational function model). The method comprises the following steps of: calculating respective RPC (Rational Polynominal Coefficient) parameter of images; performing forecast of initial positions of points to be matched, matching of approximate epipolar line geometric establishment constraints and geometric rough correction of matched window images by using the RPC parameters of the images on every pyramid image layer, deleting wrong matching points from the image matching result of every layer of pyramid by adopting regional computer network error compensation based on an RFM model; refining the RPC parameters of the images and calculating the object space coordinates of the matching points; refining the matching result to the original image layer by layer; and refining a matching result by using a least square image matching method to realize automatic and reliable matching of common points of multisource space-borne SAR images. In the method, the RFM model is introduced into automatic matching of the multisource space-borne SAR images, and the regional computer network error compensation of the RFM model is blended into the image matching process of every layer pyramid, so that wrong matching points in the matching process can be effectively deleted, and the workload of manual measurement of common points is effectively lowered.

The invention provides a data de-duplication method of a backup server. The data de-duplication method specifically comprises the following steps that a logical volume of a hard disk module of the backup server is divided to form a partition which is used for temporally storing data needing to be backed up on the server, and the partition has the data buffering function; block segmentation is carried out the buffered data in the partition, and the hash value of the buffered data is worked out with one block as a calculation unit and stored in a database; the hash values are compared, in other words, the hash value of the new data backed up each time is compared with the existing hash value in the database, if the hash value of the new data is the same as the existing hash value in the database, the new data and the data in the database are repeating data, or otherwise, the new data and the data in the database are not repeating data, and the hash value of the data block is added into a hash library. Compared with the prior art, the data de-duplication method of the backup server has the advantages that the repeating data can be effectively deleted, the storage space is greatly saved, the storage space is saved to a certain degree, and the operating cost of enterprises is reduced.

The invention discloses a rapid method and a rapid system for removing notification bar information of a mobile terminal. The method includes: S1, detecting whether a notification bar receives new notification information or not in real time, and displaying the new notification information on the notification bar if yes; S2, detecting whether a double-click is available in a notification bar area or not, judging whether time of the double-click signal is within a preset time interval or not; S3, when the time of the double-click signal is within the preset time interval, removing the new notification information in the notification bar. When a screen of the mobile terminal is lightened, a status bar area is clicked doubly, and when the area receives the double-click signal and the double-click signal is judged as an effective double-click signal, a deletion command is executed; a notification whitelist is set, when the deletion command is executed, an application notification in the whitelist is reserved, a user is allowed to check and process the notification conveniently in time and delete other push information effectively without pulling down the notification bar, user time is saved, checking efficiency is increased, and user experience is improved.

The invention provides an AP choosing method based on WLAN indoor positioning, comprising steps of measuring signal intensity of all access points in the position by a user, obtaining a complex vector for describing AP signal characteristics according to the AP signal by the system, eliminating AP candidates which are invalid for positioning according to the characteristics of the complex characteristics, calculating an optimal signal measurement strategy based on a simulation annealing algorithm according to the user-given measurement times, performing measurement on the signal of the access point according to the calculated strategy, uploading the measurement result to the server according, calculating the position of the user by the server according to the signal measurement result and returning the result back to the user. On one hand, the invention effectively eliminates the invalid AP candidate and reduces the complexity, and, on the other hand, the invention provides the optimal strategy based on the simulation annealing algorithm and effectively improves the positioning accuracy under the condition that the measurement times are limited.

The invention discloses a fast density clustering double-layer network recommendation method based on graph structure filtering. The method comprises the steps that (1) analog comment data is automatically generated through TextGAN according to historical user comment information to serve as false comments which are accurately annotated with a class mark and extremely similar to real samples; (2)historical real comments and the analog comments marked as the false comments are used as input, a graph-based virtual information filter for studying user access records is designed considering thatthe generated false comments are extremely similar to the real comments, and false users and false comments are detected through continuous iteration of confidence of users, stores and comments; and (3) in order to solve the problem of sparsity of result recommendation data, the recommendation method based on a fast density clustering double-layer network is designed. Through the method, self-adaptive selection of parameters can be realized, a good clustering result can be obtained, therefore, more effective personalized recommendation lists of users can be obtained, and the accuracy of recommendation is improved. An adversarial generative network is utilized to generate false samples extremely similar to the real comment data, and the fast density clustering double-layer network recommendation method based on graph structure filtering is efficient and reliable.

Provided is a magnetic head including a bottom pole, a top pole spaced a predetermined distance apart from the bottom pole, an inductive write coil for forming a magnetic field at the bottom and top poles, and a magnetic shield layer positioned over the top pole.

The invention discloses a pedestrian re-recognition method based on pixels and a channel attention mechanism. The pedestrian re-recognition method comprises the steps of extracting global features ofpedestrians according to a boundingbox (retrieval box) of a person; averagely dividing the pedestrian picture into two parts and three parts, and respectively extracting local features of pedestrians;and matching the extracted character features with the character information in the Galertness, and finding out the required character information. A channel and a pixel attention module are used forfeature extraction, so that the influence of background information on a retrieval result is effectively reduced; meanwhile, middle-layer supervision is further designed for the neural network, in the feature extraction process, a multi-loss function is used for supervising middle-layer feature information, and network convergence is accelerated; according to the pedestrian re-recognition networkbased on the channel attention mechanism, the pixel attention mechanism and the middle layer supervision, redundant information in figure boundbox can be effectively deleted, figure information is effectively aggregated, and therefore retrieval precision is remarkably improved.