47results about How to "The goal is obvious" patented technology

The invention discloses an infrared and visible light image fusion method based on a generation countermeasure network, the invention is characterized in that: a generating antagonistic network is established; the generating antagonistic network comprises a generator and a decider; the generator and the decider are arranged as a convolution neural network; and the fusion characteristics and the fusion rules are automatically learned in the process of training the convolution neural network; The infrared image and the visible image are simultaneously input to generate the generator in the countermeasure network. The generator performs image fusion operation and outputs the final fusion image. The invention breaks through the limitation of fusion features and rules of manual design, the fused image generated by the invention can well keep the basic radiation information of the infrared image and has abundant texture information, meanwhile, the visual effect of the fused image is good andthe saliency of the target is high.

The invention provides an illuminating device, display device, and method of manufacturing light modulation element. The illuminating device includes a light guide plate, a light source disposed on a side face of the light guide plate, and a light modulation element disposed on a surface or on inside of the light guide plate and joined to the light guide plate. The light modulation element has a pair of transparent substrates disposed apart from each other and opposed to each other, a pair of electrodes provided on surfaces of the pair of transparent substrates, and a light modulation layer provided in a gap between the pair of transparent substrates. The light modulation layer includes a first region and a second region both having optical anisotropy and having response speeds to an electric field different from each other.

The invention discloses a sea surface ship candidate region detection method based on visual saliency. The method comprises the following steps: step 1, acquiring a frequency domain feature map of anoptical remote sensing image containing a sea surface ship target by adopting an FT visual saliency model; step 2, acquiring an edge gradient feature map of the optical remote sensing image by adopting a Scharr edge detection operator; step 3, fusing the frequency domain feature map and the edge gradient feature map by adopting a Gaussian mixture function to obtain a fused feature map; and step 4,based on an otsu adaptive threshold segmentation algorithm, carrying out binarization on the fusion feature map, so that an area containing a ship target can be extracted from the image, and a sea surface ship candidate area can be obtained. The advantages of the FT visual saliency model and the Scharr edge detection operator in sea surface ship detection are fused, the influence of background noise is effectively suppressed, ship targets of all sizes are highlighted, and the candidate region extraction result is more accurate; the detection speed of the fusion model for extracting the sea surface ship candidate area is high.

An image segmentation method based on a Gaussian smoothing filter is provided. The method comprises the following steps: carrying out a weighted average operation on three components (RGB) by means of different weights according to the importance of the three components and other indexes; adopting histogram equalization to correct a histogram at first, correcting the histogram of an original image and enabling the histogram to be evenly distributed through a gray scale transformation function, and then conducting histogram equalization; conducting Gaussian smoothing filtering on the image, adopting a method utilizing only one global threshold T during a binary process, comparing the gray value of each pixel of the image with the T, and taking a foreground color if the gray value is greater than the T, otherwise, taking a background color; taking a central point P corresponding to the maximum number of pixels within L gray scale ranges as an initial mean value; checking each pixel during the i iteration, and calculating the distance between each pixel and the mean value of each gray scale, and giving each pixel the mean value closest to the class of the pixel; for j=1,2,...1, calculating a new cluster center, and updating a class mean value; and checking all the pixels one by one.

The invention provides a method and an apparatus for accurate measurement by using dual prisms. The method comprises: measuring prism A, prism B and a to-be-measured point C which are located on the same line; in the case that a linear distance SBC between the prism B and the to-be-measured point C is given, determining three-dimensional coordinates of the prism A (XA, YA, HA), and the prism B (XB, YB, HB); and measuring and calculating a slope distance SAB between the prism A and the prism B and a slope distance SBC between the prism A and the to-be-measured point C, and calculating the three-dimensional coordinates of the to-be-measured point C according to a formula (shown in the specification). According to the present invention, the method is simple, the accuracy is high, during the measurement, the need of adjusting an adjustment bubble of a measuring rod is eliminated; during measurement of a sheltered position, all one need to do is to adjust the angle direction of the measuring rod or lengthen the distance between the prism B and the to-be-measured point C according to the situation, without the need of side shots.

Disclosed is a gray scale space division method of image preprocessing based on mean value filtering. The method comprises the following steps: according to importance of RGB three components and other indexes, performing weight average operation on the three components by means of different weights; histogram correction is firstly carried out by use of histogram equalization, a histogram of an original image is corrected to be uniformly distributed by use of a gray scale conversion function, then the histogram correction is carried out; carrying out the mean value filtering on the image by use of a global threshold method in which only one global threshold T is used in a binary process, the gray scale value of each pixel of the image is compared to T, if the value is greater than T, the value is taken as a foreground color, and otherwise, the value is taken as a background value; taking center points P with maximum quantities of corresponding pixels in L gray scale grade scopes as initial mean values; and during i-th iteration, investigating each pixel, calculating the spacing between each pixel and the mean value of each gray scale grade, endowing each pixel with a mean value to a closest cluster, for j=1, 2, ...1, calculating a new cluster center, updating a cluster mean value, and investigating all the pixels one by one.

The insertion of electrically insulating paper from a continuous roll into slots of a stator created by outwardly projecting teeth is described herein. The insertion of the insulating paper is done by the insertion of prewound coils in the stator slots. The electrically insulating paper is not cut prior to its insertion in the slots, thereby completely covering the outer surface of the stator. The insertion systems and methods described herein are also optionally concerned with the insertion of interphase insulation paper between the different coils inserted in the stator slots and with the insertion of slot closing wedges.

The invention, in combination with the development of CNN frameworks, polarized hyperspectral imaging technology and dictionary pair learning, provides a novel polarized hyperspectral low-altitude reconnaissance image typical target detection method in a polarized hyperspectral low-altitude target detection simulation environment. The method is characterized by providing a dictionary pair driven CNN classifier for target detection by improving the mature Faster R-CNN in the CNN framework; using dictionary pair back propagation (DPBP) for the end-to-end learning of the dictionary pair classifier and the feature representation of CNN; using a sample weighting method to improve positioning performance; using multi-task loss for the joint training of a DPCL and boundary frame regression; introducing a polarized hyperspectral image into target detection and selecting three typical targets for testing so as to preliminarily verify the validity of the model and the sample. The method can be combined with different CNN frameworks, has high flexibility, can enhance the target-background contrast of the polarized hyperspectral image, reduces the complexity of the background to a certain extent, highlights the target, contributes to detection results, and has significant meaning to the improvement in the detection and recognition of polarized imaging targets.

The invention relates to a method for electric power system dynamic economic dispatching with correlation of multiple wind power plants being considered. The method comprises the steps of putting forward a method for generating joint distribution of power output among the multiple wind power plants based on a Copula function, constructing a two-stage band compensation power grid dynamic economic dispatching model based on the distribution, introducing a compensation expected value into an objective function, and solving the compensation expected value by using integration so as to enable the compensation expected value to be converted into a numerical model from a stochastic model, that is, enabling two-stage band compensation dynamic economic dispatching to be converted into a numerical model from a stochastic programming model, thereby quantifying impact imposed on a power grid by a stochastic property of the wind power plants, and solving optimal unit output which satisfies the objective function and the minimum impact simultaneously. According to the invention, solving is carried out by adopting the two-stage band compensation dynamic economic dispatching model, and the solving accuracy of the model is improved.

The invention relates to the field of images, in particular to an infrared and visible light image fusion method based on DLatLRR and VGG.Net. The problems of serious feature loss and non-prominent salient target in infrared and visible light image fusion are effectively solved. A source image is decomposed into a low-rank part, a salient part and sparse noise through DLatLRR, the low-rank part isfused based on a VGG16 feature extraction algorithm, and finally image reconstruction is performed on the fused low-rank part and salient part so as to obtain a fused image. The fused image of the algorithm is high in definition, distinct in hierarchy, rich in detail information and less affected by noise, the contrast of the image is high, and the salient region and the target in the scene are relatively more prominent.

A synchronous rectifier comprising a MOSFET device, and a gate driver for driving the gate of the MOSFET device, the MOSFET device comprising first and second MOSFET transistors coupled with their drain-source paths in parallel to receive an alternating current waveform for rectification by the drain- source paths of the MOSFET transistors, the first transistor having a low Rdson and the second transistor having a high Rdson whereby the apparent Rdson of the MOSFET device is increased when the current through the MOSFET device is below a threshold thereby enabling zero crossing detection.

The invention discloses an infrared image and visible light image fusion method. The method comprises the following steps of firstly, decomposing a source image by using robust principal component analysis to obtain a sparse component and a low-rank component of the source image; fusing the sparse components of the source image by using a region energy-based fusion method; and performing scale transformation on the low-rank component of the source image by adopting a non-down-sampling contourlet transformation method to obtain a low-pass sub-band and a band-pass sub-band, fusing the low-pass sub-band by adopting a region energy-based fusion rule, fusing the band-pass sub-band by adopting a gradient increasing fusion rule, and performing inverse transformation to obtain the fused low-rank component, and finally obtaining a fusion result of the infrared image and the visible light image through superposition. According to the method, the image is decomposed into different pieces of information, and the appropriate method is adopted for fusion, so that the fused image information is richer, and the image effect is better.

The invention belongs to the technical field of material preparation, and particularly relates to a two-step calendering device for graphite and a calendering method. The calendering device comprisesa main calendering structure, the main calendering structure comprises a graphite unwinding shaft, a cover film unwinding shaft, a main calendering upper roller, a cover film winding shaft, a first release film unwinding shaft and a main calendering lower roller; the calendering device further comprises an additionally-arranged secondary laminating calendering mechanism; the secondary laminating calendering mechanism comprises a secondary laminating calendering upper roller, a graphite winding shaft, a first release film winding shaft, a secondary laminating calendering lower roller, a secondrelease film unwinding shaft and a second servo motor; and the secondary laminating calendering upper roller is installed at the material outlet end of the main calendering structure, the main calendering structure is installed on an installation frame, a gap between the secondary laminating calendering upper roller and the secondary laminating calendering lower roller is controlled by a passing roller and the second servo motor, and the second release film unwinding shaft and the first release film winding shaft are fixedly installed at a material receiving end. The device provided by the invention solves the problems that graphite easily remains on a release film, calendering is insufficient, and the thickness of the graphite does not reach the standard, has a simple structure, and is convenient to use.

The invention relates to an unmanned rolling machine positioning method. The method is characterized by comprising specific steps of (1) arranging an operation area; (2) respectively acquiring imagesby an image acquisition device to perform visual ranging; and (3) calculating position coordinates of a rolling machine according to a distance between the rolling machine and a plurality of marker posts, and positioning the actual position of the rolling machine in the operation area. The method is scientific and reasonable in design, and does not depend on GPS and IMU schemes in the prior art, so the GPS and IMU are prevented from being affected due to poor signals and vibration of the rolling machine, and positioning robustness is improved. The method is advantaged in that the method can coexist with a positioning method based on the GPS and the IMU, not only can a remarkable target be provided for positioning, but further communication service can be provided for the rolling machine and a command center in a rolling machine operation area.

The invention discloses a tumbler type buoy. The buoy comprises a load-bearing seat and a buoy frame erected on the load-bearing seat, wherein the buoy frame is provided with a first chamber and a second chamber, a first foam buoyancy device is detachably mounted in the second chamber, a second foam buoyancy device and a third foam buoyancy device are detachably mounted in the first chamber, and the first, second and third foam buoyancy devices are arranged in such a manner that end surfaces are aligned correspondingly and every two side surfaces are tangent with each other; a flashing light and a sign flag are mounted on the buoy frame; a connecting ring and a rudder plate are mounted below the load-bearing seat. The buoy is applicable to all sea areas with strong wind, huge waves and variable wind directions; the condition that the buoy winds round a horizontal floating cable and then impacts a wave meter possibly can be avoided; the buoy is obvious when floating in the sea, and the flashing light is mounted to prompt passing ships at night; the buoy is sensitive to steer, and the water resistance is smaller than that of a 'transverse buoy'; no matter how the wind and the waves change, the buoy always stands towards the water and is just like a 'tumbler'; the buoy is simple in manufacturing technology, conventional in material and low in manufacturing cost.

The present invention relates to one new kind of indoor sports activity and the sports articles include wooden bat, shuttlecock and net. The shuttlecock activity is carried out normally in room and the players knock the shuttlecock in turn. The wooden bat is designed in proper size of 461-556 sq cm, thickness of 5-6 mm and weight of 175-250 g; the shuttlecock is white, 4-4.5 g weight and 6-6.5 cm long; and the net is 300-350 cm wide and 80 cm high. The playing method may be a two-player one or a four-player one.

The invention relates to the technical field of computer information, and discloses an infrared and visible light image fusion method combining potential low-rank representation and a convolutional neural network, and the method comprises the steps: carrying out the preprocessing of a visible light image and an infrared image, decomposing the image into a significant part and a low-rank part through the potential low-rank representation, and fusing the salient part and the low-rank part by using two full convolution models, and finally adding the fused salient part and the fused low-rank part to obtain a final fused image. The fusion result obtained through fusion is rich in detail information, and compared with an original low-illumination image, the scene target is clearer, and the contrast ratio of the image is improved.

An image C-mean clustering algorithm includes the steps of conducting grey transformation on an image to obtain a grey image; freely selecting c different values from 0 to 255 to serve as central values for segmenting the image into c types, wherein in other words, the values of z<(k)>[1], z<(k)>[2]...z<(k)>[c], and k is made equal to 0; dividing grey values g(x,y) (x is equal to 1, 2...M, and y is equal to 1,2...N) of pixels of all different positions in the image into a certain type in the c types one by one according to the minimum distance principle; if the equation (please see the equation in the formula) works, x is equal to 1,2...M, y is equal to 1,2...N and a value belongs to {1,2...c} exists, judging that g(x,y) belongs to omega<(k+1)>[l], wherein omega<(k+1)>[l] (l is equal to 1,2...c) is a cluster, the equation (please see the equation in the specification) represents the distance between g(x,y) and the center z<(k)>[j] of omega<(k)>[j], the superscript represents the iterative times, and then a new cluster omega<(k+1)>[j] (j is equal to 1,2...c) is generated; calculating the centers of all newly-divided types, wherein in the equation, n<(k+1)>[j] represents the number of modes contained in the type omega<(k+1)>[j]; ending if z<(k+1)>[j] is equal to omega<(k)>[j] (j is equal to 1,2...c).

The invention discloses a power distribution network reconstruction method of a particle swarm algorithm considering the number of loops of an IEEE node system, and belongs to the field of power systems. The invention aims to solve the problem that: a power distribution network reconstruction method based on an optimization algorithm cannot give consideration to search efficiency and target optimization. The power distribution network reconstruction method based on the particle swarm algorithm comprises the following steps: step 1, initializing parameters; step 2, randomly generating an initial group; step 3, evaluating each particle, and calculating the power flow of the power system; step 4, updating the particles; step 5, updating pbest; step 6, updating gbest; and step 7, judging whether t reaches the maximum number of iterations T or not, if so, outputting the gbest, ending the program, otherwise, turning to the step 4. The method is mainly adopted to reconstruct the power distribution network.

The invention discloses a laser positioning device for an electric tower. The laser positioning device comprises a laser emitting member, a reference point inspection board and a laser inspection and positioning member arranged from front to back. Laser emitted by the laser emitting member realizes perpendicular incidence to the reference point inspection board; the reference point inspection board acquires laser rays which are reflected to a laser induction sounder through a prism arranged on the laser inspection and positioning member; and a support bar is arranged at the lower part of the laser inspection and positioning member. The laser positioning device employs the characteristic of good linearity of laser and utilizes a combination of sound and light, so long-distance accurate positioning is easily realized and efficiency is high; and the laser positioning device is simple in structure, convenient to carry, good in visibility and operability and accurate in positioning, can meet requirements of primary-level power supply departments for rapid and high-efficiency construction of lines and has good promotion and application value.

The invention provides a pursuit game decision-making method for pursuers at different speeds, and the method comprises a strategy selection method for pursuers and pursuers, can enable game participants to make real-time intelligent decisions for a complex confrontation environment, and improves the team cooperation capability and game confrontation of mobile robots. According to the method, the pursuit game problem when an escaper has the speed advantage and pursuers have the number advantage is considered, the characteristics and composition conditions of a perfect surrounding formation (PEF) of the pursuers are introduced, and an escape strategy when the escaper is trapped in the perfect surrounding formation is analyzed from the nature of the perfect surrounding formation; the method is simple, convenient and visual, and successful escape can be ensured; the pursuit game problem when pursuers have the speed and number advantages is considered, the pursuers are classified into three types of trappers, interceptors and players according to the influence capacity of the trappers on the safety area, strategy selection of the pursuers and the pursuers is analyzed on the basis, and the pursuit time of the pursuers can be optimized.

The invention discloses a content recommendation method based on a rank algorithm. According to the method, model training and sequence optimization are respectively carried out by using Pointer Network and reinforcement learning, and the method sequentially comprises the following processing flows of original data, preprocessing, input layer, coding layer, decoding layer, optimizing, evaluating and loop iteration, wherein the loop iteration process is that data is optimized and then returns to the input layer to be coded, decoded, optimized and evaluated. The method has the beneficial effectsthat a rank algorithm is provided to solve the potential influence and association between items and between user sequence behaviors, so that the overall long-term click / conversion rate is optimal; on one hand, modeling can be carried out on the relation between the items, and it is avoided that related clicks / conversion rates are independently calculated for the items in recommendation; and on the other hand, the long-term sequence behavior feedback of the user can be captured, so that the long-term overall target is optimal.

An aircraft crash emergency method relates to an aircraft. The aircraft is equipped with cabins, forward and aft satellite parachutes, osprey propellers, forward and rear telescopic spring tubes; thecabin is located at the bottom of the aircraft cabin; the front and rear satellite parachutes are arranged at the top of the aircraft cabin, and the top of the front and rear satellite parachute is provided with a front and rear satellite parachute cabin cover; The propeller is provided with a top cover of the engine room; The front and rear telescopic spring tubes are arranged on the front and rear sides of the aircraft cabin front tires; A left, right, upper and low groove is provided in that windshield of the aircraft; Place multiple filter plates in the spare luggage compartment; The bottom of the cabin is provided with I-shaped beams, the left and right sides of the I-shaped beams are respectively provided with tyres, the periphery of the cabin is covered by a frame, the frame is provided with lifting hydraulic rods, and the cabin is sealed; When the air crash occurs at an altitude of 3000m, the main fuel tank is discarded in turn, the backup landing fuel tank is activated, the satellite parachute and propeller are opened and the landing gear in the abdominal cabin of the aircraft is opened automatically.

The embodiment of the invention discloses a target deduplication method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a first slice video and a second slice video which are adjacent in any time sequence, wherein the end of the first slice video has a pre-marked first calibration time period, a pre-marked second calibration time period exists at the beginning of the second slice video, and the first calibration time period and the second calibration time period are overlapped; respectively carrying out target detection and target tracking on the sub-slice video in the first calibration time period and the sub-slice video in the second calibration time period, and carrying out target calibration processing according to a target detection result and a tracking result to obtain a first calibration result and a second calibration result; and according to the first calibration result and the second calibration result, performing target deduplication processing on the first slice video and the second slice video. Therefore, the effect of target deduplication between different slice videos is realized, and the finally obtained target is ensured to be optimal.