31 results about "Pattern discrimination" patented technology

The invention discloses an improved HEVC sample point self-adaption compensation method. The BO algorithm and the EO algorithm are adopted for performing SAO filtering on images. The sample point self-adaption compensation algorithm is adopted for solving ring effects caused by transform and quantization in the current video coding standard HEVC in the loop filter technology. The current video coding standard HEVC comprises BO and EO algorithms, but sideband distribution conditions are not fully taken into consideration in the BO algorithm which only transmits four continuous sidebands. According to the invention, by use of an image histogram, the sideband distribution conditions can be sufficiently analyzed; intra-frame prediction mode type texture information is extracted in a self-adaption manner; and for different sizes of CTB, four kinds of BO filter modes are added, BO filter pattern discrimination process is improved, and the improved self-adaption compensation method is provided. The experimental results show that compared with the HM10.0, coding performance is improved; bit rate gain of chromaticity can reach -7.53%; and subjective assessment quality of image edge parts is obviously improved.

To provide a serial transfer interface for realizing a transmission of a stable and high-quality signal although there are characteristic variances due to an environment change and an LSI process, a serial transfer interface is provided at least with a signal waveform correction unit for correcting the distortion of a signal waveform, a latch unit for latching the signal waveform with a synchronous clock and outputting it to a subsequent circuit, a filter characteristic adjustment unit for changing the filter characteristic of the signal waveform correction unit in a predetermined range, a clock generation unit for generating the synchronous clock having a desired phase, and a pattern discrimination unit for detection of a test pattern and control of the filter characteristic adjustment unit and the clock generation unit.

Data classification is used to classified input items by associating the input items with one or more classes from a set of one or more classes in a data classification system, including identifying relevant features in an input item to form a feature vector for the input item, receiving at the data classification system an indication of a point-of-view, adjusting the feature vector according to the point-of-view indication or modifying a pattern discriminator (e.g., trainer and classifier) to inline-process feature vectors depending on the provided point-of-view (e.g., SVM custom kernels), and classifying the input item into the set of classes according to the point-of-view. The point-of-view data can be introduced either as a pre-process step prior to passing it off to the pattern discrimination algorithm, or can be incorporated directly into the pattern discrimination algorithm if applicable. The pattern discrimination algorithms can detect arbitrary patterns given a similarly prepared dataset during both training and subsequent classification of unclassified documents.

The invention provides a large power grid transient state stabilization analyzing method based on precision pattern discrimination. The method comprises the following steps: step S1, obtaining dynamic response data of a power grid, wherein the relevant data includes SCADA (supervisory control and data acquisition), PMU (phasor measurement unit) and network protocol structure data; step 2, carrying out characteristic extraction on the dynamic response data of the large power grid; and step 3, carrying out real-time pattern discrimination by using a DHMM (discrete hidden markov model) method. According to the method, the dynamic response characteristics of electric characteristic vectors are considered, and the pattern discrimination is carried out and the multi-dimensional characteristic analysis is implemented at the same time, thereby improving the precision and the speed in the discrimination of a manual intelligent type evaluation method, and being beneficial to the implement of the large power grid transient state stabilization analysis.

The invention discloses a two-phase flow pressure drop and noise spectrum analysis-based flow pattern discrimination method. The method is used for judging the flow pattern of a two-phase flow in a pipeline. The method comprises the steps of respectively acquiring continuous pressure-drop time-domain signals at the two ends of a measurement section of a pipeline and the two ends of a liquid pump; subjecting the continuous pressure-drop time-domain signals to the pressure-drop high-frequency sampling treatment to obtain pressure-drop time-domain figures; judging the relevance between the pressure-drop time-domain figure at the two ends of the measurement section of a pipeline and the pressure-drop time-domain figure at the two ends of the liquid pump to obtain the flow pattern of the two-phase flow. According to the technical scheme of the invention, the two-phase flow pressure drop and noise spectrum analysis-based flow pattern discrimination method has the advantage of accurate recognition effect.

The invention requests to protect a face reticulate pattern stain removal method based on a multi-task full convolutional neural network, and the method comprises the following specific steps: 1, taking a clear face image of a public face data set CelebA as a reticulate pattern-free image data set, and making a training set and a verification set; 2, cutting the reticulate pattern image, the realimage and the reticulate pattern binary mask image into image blocks with the size of 64*64; Step 3, obtaining detail layer information of the human face reticulate pattern image as model input by applying guide filtering; 4, designing a full convolutional neural network, and outputting residual error information and binary mask reticulate pattern discrimination information; 5, optimizing the lossof the real image, the reticulate pattern image and the residual error information by using the paired training data, predicting the loss of the reticulate pattern mask and the real reticulate pattern mask label, and training the model; and 6, predicting a test image of a real scene by using the model parameters obtained by training to obtain a predicted decontamination image. According to the invention, a high-quality image is provided for the subsequent operation of the face image.

Determination of inclination of positioning patterns used in bonding being made by: imaging a positioning pattern of reference chip and taking such image as reference-image; specifying a polar coordinate conversion origin for the reference-image; imaging an object (chip) of bonding to use it as an object-image, thus obtaining a relative positional-relationship with the reference-image; specifying the polar coordinate conversion origin of the object-image, so that the object-image is subjected to a polar coordinate conversion; and calculating inclination-angle from both images that have been subjected to a polar coordinate conversion; thus using a point, in which an error in position of the object of comparison detected by pattern matching between an image, which is the object of comparison obtained by imaging the object of comparison disposed in an attitude that includes positional deviation, and the reference-image, shows a minimal value, as an origin of the polar coordinate conversion.

Determination of inclination of positioning patterns used in bonding being made by: imaging a positioning pattern of reference chip and taking such image as reference-image; specifying a polar coordinate conversion origin for the reference-image; imaging an object (chip) of bonding to use it as an object-image, thus obtaining a relative positional-relationship with the reference-image; specifying the polar coordinate conversion origin of the object-image, so that the object-image is subjected to a polar coordinate conversion; and calculating inclination-angle from both images that have been subjected to a polar coordinate conversion; thus using a point, in which an error in position of the object of comparison detected by pattern matching between an image, which is the object of comparison obtained by imaging the object of comparison disposed in an attitude that includes positional deviation, and the reference-image, shows a minimal value, as an origin of the polar coordinate conversion.

The invention relates to a device for managing and controlling a single-living house. A sensor and a camera which are arranged in a privacy-invading area and a privacy-invading area are used for judging whether an old person living alone is in a room or not and judging emergency situations. To this end, the present invention discloses an exclusive housing management and control device comprising:a plurality of movement sensing units provided in a monitoring area of an exclusive housing to sense movement of an object; An electric lamp sensing unit for sensing the on / off of an electric lamp that is living alone in the housing; An action pattern discrimination unit that discriminates the action patterns of the person and the pet, which are to be sensed, by comparing the action patterns witheach other on the basis of the signal from the movement sensing unit; A position confirmation unit that generates position information and time information of the object on the basis of the signal from the movement sensing unit; A room determination unit that determines whether or not the object is in the room on the basis of the signals from the plurality of motion sensing units, the lamp sensingunit, the motion pattern recognition unit, and the position confirmation unit; And an emergency situation determination unit that determines whether or not the vehicle is in an emergency situation onthe basis of the position information and the time information generated by the position confirmation unit.

The invention discloses a distributed video compression sensing reconstruction method based on time correlation. On the basis of establishing a distributed video compression sensing model without feedback, the method makes full use of the time correlation between non-key frames of video frames, performs pattern discrimination on each block of the non-key frames, and transmits the non-key frames with the residual encoding of the previous frame; and during the reconstruction, the reconstruction mode with edgeless information is adaptively selected according to the result of the mode discrimination, and the block of each non-key frame is reconstructed, thereby avoiding unnecessary calculation of the side information. The method utilizes the previous frame of the current frame for reconstruction instead of simply using the key frame as a reference frame for reconstruction, so that the time correlation between the video frames can be effectively utilized. The method can guarantee the reconstruction quality of the video at the same total sampling rate, while reducing the system reconstruction time, and no feedback channel is used.

A feature selection apparatus, which selects features to be used to discriminate an object by a discriminator using learning data including the object, extracts a plurality of partial data from the learning data, and obtains discrimination values obtained by controlling the discriminator to process the plurality of extracted partial data as features of the plurality of partial data. The feature selection apparatus evaluates the obtained features based on discrimination degrees on a discrimination space defined by the discriminator, and selects features to be used to discriminate the object from a plurality of features obtained in association with the plurality of partial data based on an evaluation result.

The invention discloses a self-adaptive switching frequency regulator circuit which mainly solves the problem that in the prior art, a switching convertor only has high efficiency in a narrow load range. The self-adaptive switching frequency regulator circuit comprises a pattern discrimination module, a threshold selection module, fundamental oscillation logic, jitter frequency control logic and a controlled current source. The pattern discrimination module detects external feedback voltage FB to generate two comparison logic signals which are subjected to logical operation in the threshold selection module, low-threshold voltage of a comparer in the fundamental oscillation logic is determined, the fundamental oscillation logic outputs clock signals and is used for driving the jitter frequency control logic to generate a set of control signals to control output current of the controlled current source, frequency jitter is achieved, and electromagnetic interference of the switching convertor is lowered. The self-adaptive switching frequency regulator circuit is high in reliability, all functions can be integrated in a chip, and the self-adaptive switching frequency regulator circuit can be applied to various power supply management systems.

A technique for discriminating a specific pattern, such as an assist pattern, from an integrate circuit pattern of a workpiece by using transmission and reflection images of the workpiece pattern is disclosed. A pattern discrimination device includes an optical image acquisition unit for acquiring a transmissive image of a workpiece having a pattern and a reflective image of the workpiece pattern simultaneously, and a specific pattern detection unit which detects for extraction a specific pattern from among pattern shapes of the transmissive and reflective images in conformity with a distinguishing condition of the specific pattern. A workpiece pattern inspection apparatus using the device is also disclosed.

The invention relates to the field of integrated circuits and provides an electrical failure pattern discrimination device and discrimination method. The device and the method are used for discriminating and classifying a plurality of electrical failure patterns on a chip after an electrical test. In the electrical failure pattern discrimination device, a pattern extraction module is used for obtaining two electrical failure patterns; a feature comparison module is used for comparing whether the two electrical failure patterns have an inclusion and inclusion relation or not; wherein if yes, the classification priority of one electrical failure pattern belonging to one included party is higher than the classification priority of the other electrical failure pattern belonging to the includedparty, and if not, the classification priorities of the two electrical failure pattern are the same. By utilizing the electrical failure pattern discrimination device, the problem of classification errors caused by inclusion and inclusion relations of pattern features can be avoided, and the accuracy of yield analysis is improved. The invention further provides an electrical failure pattern discrimination method.

The invention provides a variance ratio-based extraction method for features of an intelligent olfaction spectrum used for characterization of variation of honey. According to the method, 5 different honey sources are selected as research samples, i.e., 1) honey of rape flowers harvested in Fuling District and Yongchuan District, Chongqing in western China, 2) honey of lychee flowers harvested in Nanning, Guangxi in south China, 3) chaste honey harvested in Miyun, Beijing, etc. in north China, 4) acacia honey harvested in Laiyang, Shandong in eastern China and 5) basswood honey harvested in Dunhua, Jilin and Harbin, Heilongjiang in northeast China. The method is characterized in that a gas sensor array employs an Fox4000 electronic nose which is composed of 18 metal-oxide semiconductor gas sensors and an HS100 headspace autosampler, a ratio of interspecific variance to intraspecific variance of a sample at each signal location of each sensor is calculated, and selection of signal locations is carried out based on the values of the variance ratios. According to the invention, the method realizes selection of signal locations through selection of the variance ratios, i.e., directly through comparison of the variance ratios of interspecific variance to intraspecific variance at every signal location, without any other pattern discrimination.

The invention discloses a distributed video compression sensing reconstruction method based on time correlation. On the basis of establishing a distributed video compression sensing model without feedback, the method makes full use of the time correlation between non-key frames of video frames, performs pattern discrimination on each block of the non-key frames, and transmits the non-key frames with the residual encoding of the previous frame; and during the reconstruction, the reconstruction mode with edgeless information is adaptively selected according to the result of the mode discrimination, and the block of each non-key frame is reconstructed, thereby avoiding unnecessary calculation of the side information. The method utilizes the previous frame of the current frame for reconstruction instead of simply using the key frame as a reference frame for reconstruction, so that the time correlation between the video frames can be effectively utilized. The method can guarantee the reconstruction quality of the video at the same total sampling rate, while reducing the system reconstruction time, and no feedback channel is used.

The invention discloses a two-phase flow pressure drop and noise spectrum analysis-based flow pattern discrimination method. The method is used for judging the flow pattern of a two-phase flow in a pipeline. The method comprises the steps of respectively acquiring continuous pressure-drop time-domain signals at the two ends of a measurement section of a pipeline and the two ends of a liquid pump; subjecting the continuous pressure-drop time-domain signals to the pressure-drop high-frequency sampling treatment to obtain pressure-drop time-domain figures; judging the relevance between the pressure-drop time-domain figure at the two ends of the measurement section of a pipeline and the pressure-drop time-domain figure at the two ends of the liquid pump to obtain the flow pattern of the two-phase flow. According to the technical scheme of the invention, the two-phase flow pressure drop and noise spectrum analysis-based flow pattern discrimination method has the advantage of accurate recognition effect.

The invention discloses a multi-coding-point hybrid coding pipeline method and a multi-coding-point hybrid coding pipeline device for video coding. The method comprises the steps of dividing an image into at least two sub-images which can be coded parallelly; and carrying out coding on image coding basic units according to a configured pipeline coding sequence for the sub-images, wherein the pipeline coding sequence is configured to be that an un-coded image coding basic unit is sequentially extracted from each sub-image in a cyclic mode. According to the invention, the image is divided into a plurality of sub-images which can be coded parallelly, the time interval of adjacent image coding basic units in each sub-image is enabled to be lengthened in the pipeline through a multi-coding-point hybrid coding pipeline, thereby being capable of eliminating dependency between the adjacent image coding basic units, and avoiding problems of pipeline waiting and the like. by adopting the method and the device disclosed by the invention, pattern discrimination, motion vector estimation and the like are not required to be carried out by using an approximation method, thereby improving the accuracy of coding pattern discrimination, and improving the compression quality of the image at the same time.

The invention provides a large power grid transient state stabilization analyzing method based on precision pattern discrimination. The method comprises the following steps: step S1, obtaining dynamic response data of a power grid, wherein the relevant data includes SCADA (supervisory control and data acquisition), PMU (phasor measurement unit) and network protocol structure data; step 2, carrying out characteristic extraction on the dynamic response data of the large power grid; and step 3, carrying out real-time pattern discrimination by using a DHMM (discrete hidden markov model) method. According to the method, the dynamic response characteristics of electric characteristic vectors are considered, and the pattern discrimination is carried out and the multi-dimensional characteristic analysis is implemented at the same time, thereby improving the precision and the speed in the discrimination of a manual intelligent type evaluation method, and being beneficial to the implement of the large power grid transient state stabilization analysis.