1321 results about "Information loss" patented technology

Apparatus and methods for efficient synaptic update in a network such as a spiking neural network. In one embodiment, the post-synaptic updates, in response to generation of a post-synaptic pulse by a post-synaptic unit, are delayed until a subsequent pre-synaptic pulse is received by the unit. Pre-synaptic updates are performed first following by the post-synaptic update, thus ensuring synaptic connection status is up-to-date. The delay update mechanism is used in conjunction with system “flush” events in order to ensure accurate network operation, and prevent loss of information under a variety of pre-synaptic and post-synaptic unit firing rates. A large network partition mechanism is used in one variant with network processing apparatus in order to enable processing of network signals in a limited functionality embedded hardware environment.

A method of maintaining informational integrity of a business to business (B2B) message in a distributed e-business environment is described. A sent message is stored a selected portion of which is flagged. A corresponding response message is then compared to the stored sent message. Based upon the comparing, when the response message matches the stored sent message, if a portion of the response message corresponding to the flagged portion is determined to be substantially missing, then the missing portion of the response message is replaced.

The invention discloses an automatic image defogging method based on dark primary color, which is used for solving the problem of information loss because the traditional defogging method highlights details by improving foggy day image contrast. The method provided by the invention comprises: A. calculating the dark primary color of the primary fog images and relevant atmosphere light value; B. according to the luminance component image of the original fog image, calculating a transmission image reflecting local fog concentration in an atmospheric scattering model; and C. determining the defogged primary image according to the fog image, the transmission image and the atmosphere light value in the atmospheric scattering model. Because of being built on the basis of a physical model, the invention can process various fog images in a self-adaption mode; and defogged images have favorable edge details and ideal contrast, and the clarifying effect is superior to the traditional defogging method based on image enhancement.

The invention discloses a map merging method of unmanned aerial vehicle visual SLAM under city complex environment. The method comprises the steps of 1, collecting an image through an RGB-D camera installed on each unmanned aerial vehicle, utilizing the unmanned aerial vehicle to conduct pretreatment on the image, and then conducting image registration; 2, constructing a visual odometer, and achieving loop detection; 3, optimizing the posture of the unmanned aerial vehicle; 4, constructing an octomap map, and achieving real-time on-line SLAM; 5, transmitting the octomap into a ground computer, merging a local octomap into a global octomap, and then transmitting the merged all-region octomap to the unmanned aerial vehicle. According to the map merging method of the unmanned aerial vehicle visual SLAM under the city complex environment, calculated quantity is reduced, real-time on-line SLAM can be achieved, and hidden danger of information losses brought by unstable wireless transmission is reduced; meanwhile, the task execution time is shortened, the task execution efficiency is improved, hidden danger brought by insufficient unmanned aerial vehicle cruising ability, finally more precise positioning can be obtained, and a more precise map can be established.

The invention discloses a color digital image enhancing and denoising method under random illumination. The method is characterized by comprising the following steps of: 1, image denoising processing, namely converting an original image from an RGB space to a YCbCr space, removing a Gaussian noise by using a Gaussian filter and removing a salt and pepper noise by performing median filter; 2, image brightness/contract stretch processing, converting the image from the RGB space to an HSI space, decomposing the image by using a two-sided filter, processing by an improved Retinex model algorithm, and obtaining a new image saturation by performing saturation compensation; and 3, performing fusion display on the image acquired after denoising the YCbCr space and the image acquired by HSI space processing. By the method, the color constancy of the image can be kept, the dynamic range of the image can be improved well, and simultaneously noises of the image can be inhibited and removed with less texture and detail information loss.

The present invention provides a ground three-dimensional laser scanning point cloud and image fusion and registration method, and the limitation of the scanning of the ground three-dimensional laser scanning technology is overcome. The point cloud data obtained by ground three-dimensional laser scanning often comprises various areas which can not be measured, point cloud holes are generated, and thus local area information of a scanned object is lost. The holes cause that a model can not realize visualization correctly, and model subsequent processing is influenced too. For the above problems, the invention aims to solve the problems through the following technical scheme that an SIFT image is used to carry out mosaic processing of collected image photos by means of an algorithm to obtain a panoramic image, the intensive reconstruction is carried out through the panoramic image to obtain the 3D point cloud data generated by the image photo, and an iterative closest point algorithm (ICP) is used to realize the registration working of laser scanning point cloud and image data generation point cloud.

A provided information handling system includes a plurality of aggregation devices configured to distribute information in a virtual link trunk and a plurality of nodes coupled to the aggregation devices. When an aggregation device receives a reboot command, that aggregation device is configured to transmit a first message to the nodes indicating that the aggregation device is rebooting, and receive a first acknowledgement message from the nodes indicating that they will not send any information to the rebooting aggregation device. The aggregation device is then configured to reboot, receive a second message from the nodes indicating the nodes are ready to receive information from the rebooted aggregation device, transmit a second acknowledgement message to the nodes indicating that the rebooted aggregation device has rebooted and is capable of receiving information, and receive information from one of the nodes for transmission to another node.

The invention discloses a super-resolution reconstruction method based on a conditional generative adversarial network, and the method specifically comprises the steps: making a low-resolution image and a corresponding high-resolution image training set by using a disclosed super-resolution image data set; constructing a conditional generative adversarial network model, using dense residual blocksin the generator network, and realizing super-resolution image reconstruction at the tail end of the generation network model by using a sub-pixel up-sampling method; inputting the training image setinto a conditional generative adversarial network for model training, and enabling a training model to converge through a perception loss function; carrying out down-sampling processing on the imagetest set to obtain a low-resolution test image; and inputting the low-resolution test image into the conditional adversarial network model to obtain a high-quality high-resolution image. The method can well solve the problems that a super-resolution image generated by a traditional generative adversarial network looks like clear, and evaluation indexes are extremely low, and meanwhile, the problems of gradient disappearance and high-frequency information loss are relieved through a dense residual network.

The present invention is a method and apparatus for compressing and decompressing data. In particular, the present invention provides for (de-)compressing naturalistic color-image and moving-image data, including high-precision and high-definition formats, with zero information loss, one-sample latency and in faster than real time on common computing platforms, resulting in doubled transmission, storage, and playback speed and doubled transmission bandwidth and storage capacity, and hence in doubled throughput for non-CPU-bound image-editing tasks in comparison with uncompressed formats. The present invention uses a nearly symmetrical compression-decompression scheme that provides temporal, spatial, and spectral compression, using a reversible condensing/decondensing filter, context reducer, and encoder/decoder. In the preferred embodiment of the invention, the compression filter is implemented as a cascade of quasilinear feedforward filters, with temporal, multidimensional spatial, and spectral stages, where appropriate, in that order, whose support consists of adjacent causal samples of the respective image. The decompressor cascades quasilinear feedback inverse filters in the reverse order. The filters can be implemented with mere integer addition, subtraction, and either one-dimensional table lookup or constant multiplication and binary shifting, depending on the computing environment Tables permit the data precision to be constrained throughout to that of the image samples. The encoder uses a table of prefix codes roughly inversely proportional in length to their probability, while the decoder uses chunked decode tables for accelerated lookup. In the fastest and simplest mode, the code tables are context-independent. For greater power, at the cost of a reduction in speed, the code tables are based on the temporal, multidimensional spatial, and spectral adjacent causal residue samples, where contexts with similar probability distributions are incoherently collapsed by a context reducer using one-dimensional lookup tables followed by implicitly multidimensional lookup tables, to minimize the overall table size. The invention's minimal resource requirements makes it ideal for implementation in either hardware or software.

The invention discloses an electrocardiogram diagnosis method and system based on a deep convolution neural network. The diagnosis method comprises the steps that a collected original electrocardiogram of the human body is preprocessed to obtain a plurality of heartbeat fragments with a preset length; the heartbeat fragments are input into a trained deep convolution neural network model, and a prediction value of each category is obtained; the category of a single heartbeat corresponding to the maximum prediction value and the time interval of the heartbeat and a previous heartbeat are recorded, and a time series is formed; on the basis of a preset mapping relation between a clinical diagnosis criterion and the time series, the time series is matched with the diagnosis criterion, and a corresponding diagnosis result is obtained. Any feature in the electrocardiogram is not required to be extracted, so that valid information loss, noise data introduction and other problems caused by manual screening and processing are avoided to the largest extent, and the influence of manual characteristic extraction on the diagnosis accuracy is reduced.

Most documents that are in use today embed or link to animated content. Presently, a large percentage of online content is hypertext markup language (HTML) and many HTML documents embed animations. The aforesaid online content is amenable to printing. However, embedding animated content in a document will lead to information loss when the document is printed. Users cannot print the animations or the videos embedded in documents. Therefore, there is provided a method and system for automatically finding animated content embedded in documents such as web pages, slide presentations, word processing documents, and PDF documents, that are being displayed to a user, replacing the animated content by a printable version, such as a keyframe, and a unique code, and assigning each animation a URL, to allow the users to retrieve the animations via a website on computer displays or mobile devices as they read the printed document.

Reproduction of stereophonic audio information over a single speaker requires summing multiple stereo channels. When signals having approximately equal magnitudes and approximately opposite phases at a frequency are added together, the audio information at the frequency is lost. To preserve areas of potential cancellation and potential audio information loss, the audio enhancement system adjusts the phase relationship between the stereophonic channels. To avoid the loss of the spatial content of the stereo signal, the audio enhancement system determines the difference information that exists between different stereophonic channels. The audio enhancement system enhances the difference information and mixes the enhanced difference information with the phase adjusted signals to generate an enhanced monophonic output.

The traffic speed counting and matching method for road traffic includes: fetching position information of mobile terminals from collected traffic data information; when the position information of the mobile terminals is lost, according to the change information of the position information of the mobile terminals, dynamic predicting and obtaining the position and speed information of the mobile terminals by using follow-up arithmetic; matching the position and speed information of the mobile terminals onto a road network to generate road traffic speed information. The road traffic speed counting and matching system is also disclosed. The method and system can provide exact traffic condition information to traffic managers and going out people.

The invention discloses a behavior recognition method based on sparse spatial-temporal characteristics. The method comprises the steps as follows: step 1, convolving an input video with an original input video by using space-time Gabor to establish a scale space; step 2, using the expressions of different scales as values of different channels of a space-time depth belief network and associatively learning characteristics of multi-scale; step 3, recognizing and classifying the behavior characteristics. The behavior recognition method of the invention inputs depth network to associatively learn the characteristics of multi-scale by establishing the scale space to improve performance of behavior recognition. The behavior recognition method of the invention introduces the thought of spatial pyramid in terms of information loss problem of a pooling operation and performs multilevel expansion to pooling output, and combines with sparse coding to fuse pyramid multilevel characteristic, thereby improving characteristic dimension output by a pooling layer, further improving the performance of the original network and improving behavior recognition rate.

The present invention relates to a method and program product for facilitating the maintenance of current bookmarks and preventing the loss of information associated with a bookmark. In one aspect, the invention bookmarks a Uniform Resource Locator (URL) associated with one or more HTML documents at a user's request and creates a database table containing each bookmarked URL. The source code of the bookmarked URL is scanned for embedded links which are stored in the table according to the related bookmarked URL. To ensure that the bookmarks are current, a periodic verification of the status of a bookmarked URL is performed. A change in the location or/and contents of the one or more bookmarked HTML documents results in one or more actions to prevent the loss of data to the user. In one embodiment, the database table is refreshed to reflect any changes to the content of the HTML documents. In another embodiment, where a bookmarked HTML document has been moved to a new URL, the table is updated with a forwarding URL, i.e., the original URL is replaced with the new URL. Where a forwarding URL is not available, a backup document containing the stored embedded links related to the original URL is created.

The invention relates to a net screen coding control method which can record plenty of data on paper. It includes net screen code embedding device which is composed by computer data process module, net screen code embedding module, key encryption module and printout module; net screen code reading device which is made up with scan input module, key decryption module, net screen code identification module and data storage module. The two devices make a system which can recode plenty of data on paper. Adopting the invention, plenty of data storage and net screen code which can recode plenty of data is realized through printing on paper or press. And confidential files' encryption and decryption is realized by using electronic files' method. Under condition of same area with two dimension bar code, the code method can record nearly ten times of information than two dimension bar and there is no limitation on occupied space and Chinese character record. It also resolves the problem of information loss because of local pollution. Data information can be embedded into image to resolve image quality destruction.

The invention discloses a building area extraction method based on LiDAR data, which belongs to the field of extraction of building through the LiDAR data and includes early-age processing of the LiDAR data, resampling of original LiDAR data, reverse iteration mathematical morphological filtering and separation of building and dense trees. The building area extraction method directly processes three-dimensional (3D) point cloud data instead of converting the point cloud into depth images, avoids information loss and added calculation quantity in the conversion process, simultaneously utilizesdifferent windows to conduct mathematical morphological filtering operation through reverse gradual iteration, basically removes effects of terrain fluctuation on the building in the mathematical morphological filtering and obtains high extraction accuracy. The building area extraction method can quickly and accurately extract LiDAR points belonging to the building area from a large range of LiDAR points and is capable of providing reliable data support for urban three-dimensional modeling.

The invention discloses a co-prime array DOA (direction of arrival) estimation method based on interpolation virtual array covariance matrix Toeplitz reconstruction, and mainly solves a problem of information loss caused by the heterogeneity in a virtual array in the prior art. The method comprises the implementation steps: constructing a co-prime array at a receiving end; receiving an incident signal through the co-prime array, and carrying out the modeling; calculating an equivalent virtual signal corresponding to the signal received by the co-prime array; constructing an interpolation virtual array and carrying out the modeling; constructing a multi-sampling snapshot signals of the interpolation virtual array and a sampling covariance matrix; constructing a projection matrix, and defining projection calculation related with the projection matrix; constructing a reference covariance matrix according to all information in an original virtual array, designing an optimization problem based on the interpolation virtual array covariance matrix Toeplitz reconstruction, and solving the optimization problem; and carrying out the DOA estimation according to the reconstructed interpolation virtual array covariance matrix. The method improves the freedom degree and resolution of signal DOA estimation, and can be used for the passive positioning and target detection.

The invention provides a BIM (Building Information Modeling) platform-based numerical control machining pretreatment method of a non-standard building enclosure component. The problem of information loss between every two sub-processes of a numerical control machining process of the non-standard building enclosure component and the problem of associated conversion of a two-dimensional detail and a three-dimensional model of the non-standard component are solved through the three steps of building geometric shape pretreatment, building component unit deep design and machining data processing and output.

The invention relates to an image semantic segmentation method based on a multi-layer information fusion full convolutional neural network. The method comprises the following steps: constructing the multi-information fusion full convolutional neural network; Preprocessing the training picture of the data set, and inputting a preprocessing result into a neural network for training to obtain an image semantic segmentation model; Inputting the to-be-tested image into the image semantic segmentation model, performing one-time forward propagation, and outputting a semantic segmentation result in anend-to-end manner. Basic depth features of the image are extracted by using a convolutional neural network model; According to the method, the features are divided into the low-level features and thehigh-level features, and the low-level features and the high-level features are fused into the enhanced depth features, so that the problems of low image semantic segmentation accuracy and image spatial detail information loss can be effectively solved, and finally, a better image semantic segmentation result is obtained.

The invention discloses a moving object extraction method based on superpixel division and an optical flow method, and mainly solves the problems of more noises, high-frequency information loss, inaccurate boundary and the like of the existing moving object extraction method. The implementation steps of the method are as follows: (1), inputting an image, and pre-dividing the image into a superpixel set S to obtain a mark sheet I 2; (2), taking images of two adjacent frames in a video sequence and determining a rough position of a moving object by a Horn-Schunck optical flow method; (3), using the optical flow method to obtain the speed u in the horizontal direction and the speed v in the vertical direction, wherein V is speed amplitude of the optical flow method; (4) performing median filtering, Gauss filtering, binarization operation and morphology opening and closing operation on the optical flow result V to obtain V4; (5) using a superpixel division result to further correct the optical flow result, and extracting to obtain the accurate moving object. Superpixels belonging to a moving area are extracted accurately. Simulation experiments show that compared with the prior art, the moving object extraction method has the advantages of simple operation, small noise, clear boundary and the like, and can be used for extracting the moving object in the video sequence.

The invention discloses a CTP direct platemaking method and equipment, which is characterized by the following: adapting ink-jet image-forming elementary to spray the ink-wet on the hydrophilic plate surface to form the ink-wet information record area; fixing the printed information on the printing surface through optical solidification or heat solidification. The invention reduces the information loss and simplifies the developing course, which saves the film and subsequent developing craft.

This invitation discloses a method of encoding/decoding a color QR (Quick Response) code. The method maintains the reliability and robustness of a standard black and white QR code, and employs a lossless compression algorithm to make the data capacity of a color QR code much larger than the data capacity of other colored two-dimensional code of a same kind. In addition, encoding colors are not required to be the most distant from each other in an RGB color space in order to enhance color resolution. A process of encoding/decoding a color QR code does not require color space transfer, i.e., color information loss can be avoided. Color QR cod decoding has no special requirements for ambient lighting, and does not need to utilize reference colors as a palette, thereby greatly reducing computational complexity, and obtaining 100% decoding accuracy.

A building safety monitoring system by using radio frequency identification (RFID) comprises a monitoring unit, an information management center server and an alarm unit. The monitoring unit comprises an RFID reader and a radio frequency label; the RFID reader is arranged at the boundary of an area to be monitored to detect the radio frequency label information from personnel or objects with the radio frequency label entering the monitored area and to send the detected radio frequency label information to the information management center server through a wire/wireless network; the information management center server stores the radio frequency label information, makes real-time processing to the monitored data according to a predetermined mechanism and generates alarm through the alarm unit if the radio frequency label is damaged, has the situation of information loss, abnormal movement or entering the restricted area, and the like. The building safety monitoring system has the characteristics that the information management center server can monitor the situations that the personal and the objects with the radio frequency label come in/come out of the building in real time, thus realizing the real-time safety monitoring of the building.

The invention belongs to the technical field of information security, and particularly relates to a color image encryption method based on cellular neural network hyperchaos and a DNA sequence. The method provided by the invention comprises the steps of separating red, green and blue three primary color components of a color plaintext image; updating and generating parameters and initial values of a six-order cellular neural network hyperchaotic system and a Logistic-Sine mapping system through the plaintext image, respectively carrying out iterative operation on the two chaotic systems, and obtaining red, green and blue components of an encrypted image according to a DNA encoding rule and a DNA decoding rule; and finally, changing the pixel values of the encrypted image through key stream and a bitwise XOR operation to obtain a final ciphertext image. The decryption is a reverse operation of the encryption process. Compared with the existing image encryption method, the color image encryption method provided by the invention has the advantages of high security, good encryption effect, strong robustness, no information loss and the like, and thus being capable of being widely used in military, remote sensing, remote medical treatment, commerce and other fields.