551results about How to "Accurate division" patented technology

The invention discloses a dynamic indoor region coverage division method and device for a mobile robot. The dynamic indoor region coverage division method at least includes that scanning each row of a raster map to divide the indoor region for two times, dividing the indoor region into an independent sub-region block and an independent region block, wherein the independent region block comprises a plurality of adjacent independent sub-region blocks; acquiring the topology planning sequence of the independent sub-region block and the topology planning sequence of each independent sub-region block of the independent region block based on a reverse searching mode and a minimum tree principle; acquiring the optimal route of the mobile robot in the indoor region based on a Dijkstra algorithm according to the topology planning sequences. The dynamic indoor region coverage division method and device for the mobile robot start from the environment cognition habits of the human to divide the indoor environment for two times, the completeness of the region with a certain function in the environment is guaranteed, and meanwhile, the region with a certain function is divided into the independent sub-regions where the mobile robot can walk; the dynamic indoor region coverage division method and device for the mobile robot conform to the robot thought.

A method and system for characterizing asphaltene gradients of a reservoir of interest and analyzing properties of the reservoir of interest based upon such asphaltene gradients. The analysis employs a correlation that relates insoluble asphaltene concentration to spectrophotometry measurement data measured at depth.

A method and system for characterizing compositional and fluid property gradients of a reservoir of interest and analyzing properties of the reservoir of interest based upon such gradients.

The invention relates to a knowledge graph construction method based on deep learning. The method comprises the steps that a target text statement is given, and a two-way long short term memory recurrent neural network model and a conditional random field model are used to recognize target entities in the target text statement; a context sensitive two-way long short term memory recurrent neural network model and a feedforward neural network model are used to extract the relation between every two target entities; a vector space model is used to normalize the target entities, and the normalized target entities are mapped to a concept; and a knowledge graph is constructed according to the target entities, the relation between the target entities and the concept. According to the method, the deep learning technology is applied to construction of the knowledge graph, entity recognition models of a two-way recurrent neural network and a conditional random field are adopted to recognize the target entities in the target text statement, feature engineering in the entity recognition process and the relation extraction process is reduced, the burden and trouble brought by manual design and feature adjustment are relieved, and knowledge in a text is mined precisely.

The invention discloses an image processing method, an image processing device and electronic equipment and belongs to the field of image processing. The method comprises the steps of obtaining an image and a depth value of each pixel point of the image; determining a concern point of the image; for each pixel point of the image, determining the type of the pixel point according to the distance between the pixel point and the concern point and the difference value of the depth value of the pixel point and the depth value of the concern point, wherein the type comprises a background sample point and a foreground sample point; according to a preset image processing method, processing the pixel points corresponding to the background sample point and / or the foreground sample point. According to the image processing method, the image processing device and the electronic equipment, the problems that a blurring region is not reasonable to determine and the blurring effect is not good in a background blurring processing mode which is related to a background technology are solved, the foreground and the background of the image are precisely divided, and when the image processing method is applied to the backing blurring processing, the blurring region is more reasonable to determine, and the blurring effect is improved.

The invention provides a method for quickly recognizing carbonate formation lithologies while drilling. The method includes the first step that the different lithologies are judged; the second step that rock debris of the different lithologies are sampled and are analyzed through the X-ray fluorescence element logging technology, and the Ca element pulse content and the Mg element pulse content are counted; the third step that rock debris of the different lithology centers are sampled, the Mg pulse content and the Ca pulse content of the different lithology centers are counted, and the average interval between the Mg pulse content and the Mg pulse content at the lithology center and the average interval between the Ca pulse content and the Ca pulse content at the lithology center are calculated; the fourth step that the Ca pulse content average value and the Mg pulse content average value of different lithologies are calculated respectively, then logging lithology recognition standards are obtained, and a lithology interpretation chart is established. The method achieves accurate recognition of the lithologies while drilling, judges that whether a horizontal well track passes through dolomite or not in time, and then provides a scientific basis for the necessity of adjustment of a track of an undrilled well segment and for predicament of the track of the undrilled well segment.

The invention discloses a three-dimensional structural description method of hepatic vascular system, which belongs to the field of medical liver division. The method comprises the following steps of: firstly, dividing a hepatic image and a hepatic vascular image, structurally analyzing the hepatic vascular three-dimensional image, skeletonizing the liver and the blood vessel, and marking the skeletonized voxel points; next, storing the marked voxel points to data structure of multi-branch tree; then, distinguishing main and branch blood vessels according to master slave relation of the voxelpoints in the multi-branch tree; finally, dividing the liver body into multiple liver segments according to relation between the blood vessels in the hepatic vascular system. By the three-dimensionalstructural description method of hepatic vascular system, accurate division of liver is realized so that guidance is provided for accurate removal of liver.

Each crest-shape distribution region is sectioned in accordance with a value of a color obtained from extracted elements such as hue, saturation and lightness. A characteristic amount at each of a plurality of positions of an image including a designated eye is calculated, on the basis of values of obtained characteristic amounts, an image of a pupil portion is extracted, and red-eye correction processing is carried out.

The invention relates to a character detection and recognition method for boarding pass information verification, and belongs to the field of computer vision. The method comprises the following steps:S1, reading a boarding pass image, and obtaining a boarding pass test image and a training image; S2, positioning each text block through a text line detection method of a multi-task full convolutional neural network model based on a fuzzy region; S3, through text recognition model learning based on a CTC and a self-attention mechanism, realizing recognition of a text line, namely a positioned text block; S4, establishing a boarding pass common text library so as to learn an n-gram language model, and assisting in optimizing a text line recognition result. The boarding pass character information is automatically detected and recognized, Chinese and English mixed text line recognition is achieved, and more comprehensive personal information is obtained.

The invention discloses an adaptive optimal envelope demodulation method, which is characterized by comprising the following steps: bearing fault vibration acceleration signals are acquired; improved harmonic wavelet packet transform is carried out on the signals; an improved harmonic wavelet packet kurtosis graph fused with energy indexes is drawn; the optimal frequency band is extracted according to the maximal spectral kurtosis in the kurtosis graph; modular operation is carried out on wavelet coefficients of the optimal frequency band to obtain an envelope, and FFT transform is carried out on the envelope to obtain an envelope spectrum; refinement is carried out on the envelope spectrum, and a fault type of the bearing is determined in the refined envelope spectrum. Two aspects of the prior art are improved: on one hand, conventional harmonic wavelet packet transform is firstly improved, the frequency band can be divided more precisely, the improved harmonic wavelet packet transform is combined with the kurtosis graph, the improved harmonic wavelet packet kurtosis graph is formed, the ability of detecting weak transient fault impact by the kurtosis graph is enhanced, and the application effects are improved; and on the other hand, energy information is fused in the kurtosis graph, and robustness of the kurtosis graph is improved.

The invention provides an intelligent car light control method based on cloud computing. The method comprises the steps: establishing car light control modes; transmitting car speed and car concrete position coordinates detected by a vehicle-mounted navigator to a cloud server by virtue of a GPS (global positioning system) in real time; determining which kind of section of a highway where the car is positioned by matching the car position coordinates with a cloud map by the cloud server, and calculating road condition information in next set time period according to the car speed; determining one car light control mode according to the road condition information and the type of the section of the highway in the next set time period, and controlling the lighting direction of a car light in real time. According to the scheme, first of all the comprehensively concrete car light control modes are established, the types of the section of the highway where the car is positioned is determined by matching the car coordinates and the cloud map by the cloud server, and the road condition information of the next section of the high way is calculated in advance, so the lighting mode of the car light can be adjusted in advance and in time; based on the cloud computing, the response speed is high, and the timeliness is high; meanwhile, the car light control modes are set according to the types of the section of the highway and the road condition information, and lighting requirements of various road conditions can be met.

A hybrid electric vehicle is equipped with an engine output system that makes the engine generate a driving force and outputs the driving force of the engine and a motor output system that makes an electric motor generate a driving force and outputs the driving force of the electric motor, and is capable of transmitting to driving wheels the driving forces outputted from the respective systems. If a failure of the motor output system is not detected, a vehicle ECU sets the gear of an automatic transmission for start-up of the vehicle to a first gear. If the failure is detected, the vehicle ECU sets the gear of the automatic transmission for start-up the vehicle to a second gear that is lower than the first gear.

The invention provides a route planning method for a moving carrier and belongs to the field of navigation. The method comprises the following steps: taking a grid as a minimal unit for performing partitioning treatment on an operation area of the moving carrier, thereby acquiring operation blocks; performing reciprocating operation in each operation block in an ergodic manner; performing trans-block operation after the moving carrier finishes the operation in each operation block, and performing reciprocating operation in another operation block in the same ergodic manner. The moving carrieris capable of acquiring a plurality of operation blocks through a block cutting algorithm on the basis of an electronic grid map of the known information and the operation routes in the blocks are planned in each operation block through a reciprocating traversing route planning algorithm; the cutting sequence between the blocks is planned through a trans-block operation sequence planning algorithmafter the operation is finished in the present block; various algorithms are utilized to accurately divide the routes in the operation area and the working efficiency can be finally promoted.

The invention provides a foggy day detecting method based on an image color spatial feature. The method comprises the following steps of first step, obtaining a background picture through a video image or a single image; step 2, performing color space conversion for the background picture, and extracting the color space feature: firstly performing color space conversion for the background picture, converting from an RGB (red-green-blue) color space into an HSV (hue, saturation, value) color space, and extracting the features of various components of the HSV according to the information included image; and step 3, dividing the weather information included image into a non-foggy day, a little foggy day and a dense foggy day according to the identification conditions: at first, if the identification condition 1 is met, the weather is the dense foggy day, otherwise the identification is continued; secondly, if the identification condition 2 is met, the weather is the non-foggy day, otherwise, the identification is continued; and finally, if the identification condition 3 is met, the weather is the little foggy day, otherwise, the weather is the dense foggy day. The method provided by the invention is suitable for being used for monitoring the foggy day in expressways, particularly pre-warning the emergency of agglomerate fog in partial road segments, thus, the safe road driving can be ensured.

A bypass duct portion is integrally provided in a casing of an EGR cooler so that heat distortion generated at a part of the casing when bypassing of an exhaust gas is rationally absorbed, and the EGR cooler body and a valve case are brazed / fixed all together so as to improve strength of the valve case, whereby, the bypass duct portion is formed between an inner surface of the casing and the core, a switch is provided for switching and guiding the exhaust gas to either of the core or the bypass duct portion, and a large number of outer ribs formed in the circumferential direction respectively are arranged side by side while being separated from each other in the longitudinal direction in the bypass duct portion of the casing so as to constitute a heat stress absorbing portion. And a cylindrical valve case is integrally formed by deep drawing of a thin metal plate by a press machine, a pair of slits are provided at the rear end of the valve case, both edges of an intra-valve partition plate are inserted into the slits, support projection portions are provided on both faces of the both edge portions of the intra-valve partition plate, and the edge of the slit is supported by the support projection portion. And an opening of the valve case is integrally brazed / fixed to an opening of a header portion of the casing.

A method, device, and system for polarization division multiplexing (PDM) and polarization division demultiplexing are provided in the field of communication and transmission. The device for polarization division demultiplexing includes a polarization controller (PC), a polarization beam splitter (PBS), a detection control module, an optoelectronic receiver 1, and an optoelectronic receiver 2. The PC is adapted to receive a PDM optical signal carrying an identification signal and perform polarization control on the PDM optical signal. The PBS is adapted to perform polarization division on the PDM optical signal carrying the identification signal after the polarization control. The detection control module is adapted to perform identification signal detection on the optical signal after the polarization division to obtain a power of the identification signal, and output a polarization control signal to control the PC according to a power change of the identification signal. The optoelectronic receiver 1 and the optoelectronic receiver 2 are adapted to perform demodulation reception on an X-polarization branch optical signal and a Y-polarization branch optical signal respectively to obtain a first original signal and a second original signal. Thereby, during polarization division demultiplexing, reversal of two demultiplexed polarization branches is effectively avoided.

The invention provides a method for detecting skin colors and the pigmentation situation of skin. The effect of conducting color division on a skin image in a Lab color space is superior to a skin color dividing effect in an RGB color space. Especially when skin colors have similar brightness values and different tone values, division is very difficult in the RGB color space, but a good division effect is achieved in the Lab color space. In addition, more edge noise can be removed after the skin image is subjected to median filtering treatment. Furthermore, the exposure gain and white balance parameters of an image acquisition device to be calibrated are adjusted in the mode of establishing a standard device till the differences between testing component values and standard threshold values are smaller than the same error value. The lighting influence is effectively overcome, skin colors in the skin image is accurately divided, and the pigmentation situation of the skin is analyzed.

The invention discloses multi-bridge static sounding equipment which comprises a static sounding rod and a force applying device, wherein a probe is arranged at the bottom end of a rod body; the force applying device is positioned above the static sounding rod and applies force to the static sounding rod; and a conical tip resistance sensor for measuring the resistance of a conical tip and a side wall friction resistance sensor for measuring the side wall friction resistance are arranged on the probe. The multi-bridge static sounding equipment is characterized in that the static sounding rod further comprises a microcamera for underground shooting and a plurality of sensors; the sensors are respectively used for measuring the pore water pressure, the temperature, the side pressure, the inclination, water content, the seismic velocity and seismic acceleration; and the sensors can be arranged in a connector and can be sequentially connected according to the requirement of test projects or can be directly and fixedly arranged inside the rod body of the static sounding rod or can be integrated on the probe to form the multifunctional probe. Due to the adoption of the technical scheme provided by the invention, one test process can be used for testing a large amount of projects so as to obtain abundant underground geotechnical information. The invention further discloses a multi-bridge static sounding test method.

An adaptive phase-locked loop (PLL) circuit produces an output signal having a frequency in reference to the frequency of a reference signal. The PLL circuit includes an oscillator configured to generate the output signal according to a frequency control signal, and a processing circuit configured to generate a feedback signal deriving from the output signal. An adjustable shift circuit is provided to time-shift the feedback signal. The PLL further includes a phase comparison circuit configured to generate a phase error signal indicating a phase error between the time-shifted feedback signal and the reference signal, and a control circuit configured to generate the frequency control signal based on the phase error signal. The adjustable shift circuit adjusts a time-shift amount to time-shift the feedback signal according to the phase error signal.

The invention relates to a photo processing method and a photo processing device. The method comprises the steps of grouping to-be-processed photos according to preset rules, detecting the quality of each group of to-be-processed photos to get the quality level of the group of to-be-processed photos, and storing the to-be-processed photos according to the quality level. By implementing the technical scheme, the storage space of a terminal or server is saved, and the storage pressure is reduced. Meanwhile, photos of high quality are screened out accurately for users, and the photos of high quality can be stored accurately and completely.

Method for producing disposable diaper-pants having openable and resealable side panels. Absorption bodies are applied on a continuous web of inner or outer coversheet material so that front portions and rear portions of adjacent diaper-pants blanks in a web are directed toward each other. A continuous web of outer or inner coversheet material is applied to and secured to the web with absorption bodies. Separate side panels connected to each other by a detachable and resealable connection are secured to side portions of the adjacent front portions or rear portions of the diaper pants. Each diaper-pants blank with side panels is cut from the web and folded about a transverse axis in the crotch with the front and rear edges lying against each other. The side panels of each blank are folded toward and secured to side portions of the rear or front portion which have no side panel.

The invention discloses a spectrum sensing algorithm based on variational mode decomposition, and solves the problem that a signal at a receiving end is interfered by a noise background in the prior art. The method comprises the following steps of: 1, generating a simulation signal BPSK; 2, taking the mean value of the instantaneous frequencies of the components as a decomposition parameter, determining an optimal mode decomposition number K according to a change curve of the decomposition parameter, and setting an appropriate penalty factor alpha; 3, performing variational mode decompositionon the BPSK signal according to the obtained decomposition parameters; 4, respectively carrying out power spectrum estimation on the obtained L intrinsic modes; 5, taking the ratio of the sum of the spectral line intensities of the intrinsic modes to the sum of intensities of all the intrinsic modes as a test statistic; and 6, comparing the obtained test statistics with a judgment threshold, and making a final judgment. According to the method, the equivalent band-pass filtering characteristic and the Wiener filtering structure of variational mode decomposition are utilized, frequency bands are better divided, and denoising processing is better carried out; and compared with a traditional power spectrum segmented cancellation algorithm, the detection performance can be remarkably improved.

Provided is a method for effectively segmenting a hyperspectral oil-spill image. The method comprises steps of: defining an initial level set function and other related functions; acquiring a new fitting item in combination with a Fisher criterion; constructing an edge stop function to obtain a new length item; performing improvement in combination with an end member extraction algorithm; introducing a level set regular item to prevent reinitialization of the level set function; minimizing an energy function to obtain an Euler-Lagrange equation; setting parameters; selecting a display band and an initial contour; displaying a segmentation result graph; calculating various segmentation precision evaluation indexes; comparing and evaluating the accuracy of the segmentation results. The method can classify a target area in a simulated hyperspectral image and a real hyperspectral image, and effectively segments the hyperspectral oil-spill image with boundary blur and noise, improves the segmentation accuracy of the hyperspectral image, obtain a more accurate classification effect, makes the parameter change more stable, makes the contour curve more accurate, obtains the continuous and closed boundary contour, and has higher precision of segmentation.

The invention relates to an image processing method, device and terminal, and the method comprises the steps: carrying out the scale change of a first image and a second image, and obtaining space representation sequences at the two scales, wherein the first and second images have overlapping parts; respectively extracting feature points based on pixels in the two space representation sequences, and obtaining feature points of all scales corresponding to the first and second images; carrying out the clustering of the feature points of all scales into different clusters based on the similarity of feature points of the same scale; respectively determining matching points based on the feature points in the clusters in the first and second images; and carrying out jointing and fusion of the two images based on the matching points. According to the embodiment of the invention, the method achieves the effective detection of cracks and grooves on a highway pavement, is high in accuracy, is good in instantaneity, and facilitates the formulation of a repair strategy for a broken pavement.

The invention relates to a KNN (K-Nearest Neighbor) sorting algorithm based method for correcting and segmenting the grayscale nonuniformity of an MR (Magnetic Resonance) image, belonging to the field of image processing. The method comprises the following steps of: firstly constructing a grayscale nonuniform field model by utilizing surface fitting knowledge and using a group of orthonormalization basis functions, and establishing energy functions; and then solving model parameters according to an energy function minimization principle to realize grayscale nonuniformity correction and image segmentation, wherein subordinate functions are solved by adopting an iterative algorithm and the KNN algorithm in the model parameter solving process, therefore a partial volume effect is greatly reduced while a grayscale nonuniform field is eliminated, and the influence of noises on the correction and the segmentation of the grayscale nonuniformity of the MR image is reduced. The subordinate functions are solved with KNN through the following steps of: firstly acquiring an accurate smooth normalization histogram by using a kernel estimation algorithm; then respectively solving a threshold value TCG between cerebrospinal fluids and gray matters and a threshold value TGW between the gray matters and white matters by using a maximum between-cluster variance method; carrying out rough sorting on the KNN sorting algorithm by utilizing the two threshold values; and finally accurately sorting points to be fixed by adopting the traditional KNN sorting algorithm.