47results about How to "Improve detection capabilities" patented technology

The invention discloses a road central isolation belt detection method based on an automobile anti-collision radar. The detection method comprising the following implementation steps of: (1) transmitting a signal; (2) receiving an echo signal; (3) generating an intermediate frequency signal; (4) processing a two-dimensional signal; (5) detecting two-dimensional constant false alarm; (6) determining the position and speed of a moving target vehicle; (7) detecting one-dimensional constant false alarm; (8) determining the positions of a static target vehicle and a central isolation belt; (9) comparing the position relation between the target vehicle and the central isolation belt; and (10) conducting analysis processing on anti-collision early warning. The road central isolation belt detection method not only can well detect the position and speed of the moving target vehicle, but also can well detect the positions of the static target vehicle and the road central isolation belt so as to identify the vehicles arriving at and departing from a lane, gives consideration to the moving target residual information in detection results and false-alarm information in an early warning system, has good real-time property and high detection precision, and can well assist a driver so as to ensure the driving safety, prevent automobile collision. The road central isolation belt detection method can be applied in the fields such as automobile anti-collision, navigation, automatic driving and the like in an expressway environment.

The invention discloses a fire point detection method. The method realizes fire point detection based on VIIRS 375m data by using spatial information and spectral information of the VIIRS 375m data. The method comprises the following steps: acquiring data of I1-I5 bands of an NPP satellite VIIRS sensor, wherein data of I1-I3 band is pixel reflectivity data, and data of I4 and I5 bands is pixel brightness and temperature data; determining absolute fire point pixels according to the brightness and temperature; determining potential fire point pixels according to the brightness and temperature difference of the adjacent bands; selecting candidate fire point pixels from the potential fire point pixels by using a sampling window analysis method; selecting nominal confidence fire point pixels from the candidate fire point pixels by using a context analysis method; and selecting a low confidence fire point pixel and a high confidence fire point pixel from the absolute fire point pixels by using a minimum sampling window analysis method. The method makes up the shortages of AVHRR and MODIS data on the aspect of spatial resolution, improves the detection capability on smaller fire points, and simultaneously improves the dynamic monitoring capability on large fire.

The present invention discloses a phase-coherent accumulation detection method used for a uniform acceleration moving target and belongs to the radar technical field. According to the method of the invention, a PD radar is adopted to transmit linear frequency modulation signals; pulse compression is performed on received echo signals containing a target; coordinate shift transformation is performed on the echo signals which have been subjected to pulse compression, so that the migration of the target can be corrected; and fractional-order Fourier transformation is used to eliminate the Dopplermigration of the target and achieve the phase-coherent accumulation of energy. Since the amplitude and phase information of the echoes of the target is utilized to perform long-time phase-coherent accumulation, noises can be effectively suppressed, and the detection performance of the radar for a weak target can be improved; and the fractional-order Fourier transformation can be realized throughfast Fourier transformation, and therefore, the amount of computation can be greatly reduced, and the rapid detection of the radar for the weak target can be facilitated.

The invention relates to the field of radar signal processing and especially relates to a radar anti-interference method by utilizing polarization cancellation. In the method, through determining a cancellation main channel and an accessory channel, and then, by utilizing the main channel and the accessory channel as well as channel weight coefficients thereof, no-interference signals are obtained after cancellation. The method is especially suitable for escort self-defense noise interference and general clutter interference; signal-to-clutter-noise ratio of the system can be greatly improved, detection of follow-up radar signal processing is convenient, and detection capability of the radar can be effectively improved under the complex electromagnetic environment.

A defect map image generating unit (72) of a defect inspecting device (100) generates a defect map image by combining a plurality of processed images generated by a processed image generating unit (61). The defect map image generating unit (72) has a coordinate calculating unit (721), an integrating unit (722), and a brightness setting unit (723). The coordinate calculating unit (721) calculates the coordinates of each pixel in the defect map image on the basis of the coordinates of each pixel in each processed image, the transport speed of a sheet body (2), and the frame rate set in the imaging device (5). The integrating unit (722) finds the number of defective pixels from among the pixels that had the same coordinates calculated by the coordinate calculating unit (721) and the total of gradation values in the defective pixel. The brightness setting unit (723) sets the brightness for each pixel in the defect map image according to the calculated value by the integrating unit (722).

The invention discloses a multi-perspective stereoscopic radiation imaging system and a method. The system comprises a ray source and a collimator, wherein emitted ray from the ray source passes through the collimator and form at least two ray beams and angle between any two adjacent ray beams is 3-15 DEG C; a detector system for receiving the rays passing through detected objects, transiting the ray into digital signals and sending to an image data acquisition system; a data process system for processing the image data; and an image display system for displaying the processed images, wherein the detector system comprises at least two detector arrays, images obtained by any two sets of the detector can generate a stereoscopic image of a viewing angle, and images of multiple sets of the detectors can obtain stereoscopic images of a plurality of viewing angles. Compared with single-perspective detection apparatus, the system provided by the invention can realize multi-perspective stereoscopic imaging of the detected objects through a plurality of detector arrays and the collimator, and can distinguish overlapped objects at back and forth in the objects, determine a concrete position of suspicious objects, and improve detection capacity.

The invention relates to an SRDF (Space-Range-Doppler Focus) moving object accumulation detection method for a frequency diverse array radar, and belongs to the technical field of radar signal processing and detection. The method comprises the steps: carrying out the echo demodulation and matched filtering of the frequency diverse array radar, constructing a distance-azimuth two-dimensional vectorof a receiving array element signal; realizing distance/azimuth joint estimation based on a spatial spectrum estimation algorithm; implementing the high-resolution sparse domain Doppler extraction based on sparse fractional Fourier transform to complete the space-frequency focusing processing of a moving object; constructing a space-range frequency domain detection unit map, and detecting the moving object. The method fully utilizes the flexible freedom degree and energy aggregation of the frequency diverse array radar in space, distance and Doppler, achieves the coherent projection and SRDFin a multi-dimensional space, integrates the pulse compression, angle estimation and Doppler filtering of the conventional radar signal processing, is high in accumulation gain and parameter estimation accuracy, and can improve the radar moving target detection capability in complex environments.

The invention provides an automobile remote detection method. The method comprises the following steps of: storing a detection target of the vehicle and a semantic matching rule corresponding to the detection target in a vehicle defect semantic recognition rule base; determining a detection item according to detection needs, obtaining a detection target corresponding to the detection item, detecting the detection target of the vehicle through a detection tool, and submitting a defect preliminary detection report of the vehicle obtained through detection to a background server; And allowing thebackground server to perform semantic analysis on the text content in the defect preliminary detection report by using a semantic matching rule to obtain vehicle defect description key information, and obtaining a vehicle assessment report based on the vehicle defect description key information. According to the method, the vehicle defect semantic recognition rule base is preset, the semantic matching rule corresponding to the detection target is designed and utilized, non-standard voice and character input of a detector is achieved, the detector is automatically converted into standard vehicle condition information, and extremely high flexibility and convenience are achieved.

The invention relates to a system and a method for monitoring a moving target on the ground by a marine radar. The system comprises the marine radar, a radar signal interface and a target monitoring processor (a computer), wherein the marine radar transmits a compressed microwave probe pulse and receives a detection echo from a monitoring area; the radar signal interface realizes type conversion, digital acquisition and USB digital transmission of a radar signal; and the target monitoring processor receives and processes radar image data through a USB interface and monitors the moving target on the ground. The method comprises steps as follows: frame formatting of radar signal digital acquisition data, detection of real-time dynamitic reference image, difference image and the moving target and detection and alarming of a space shielding image and the moving target. The ground moving target monitoring system suitable for safety monitoring of various lands is formed by utilizing the general marine radar and a corresponding signal receiving and processing method. By means of the monitoring system and the method, the marine radar can be applied to the land echoing environment, and the safety efficiency of the marine radar applied in the land is improved.

The invention provides a method for realizing the high precision angle measurement technique based on the amplitude single pulse. According to the target processing activation time criterion, the adjacent two response signal amplitude fluctuation correlation criterion, the sign bit revision criterion and the equal amplitude value rejection criterion, original data of the target are screened or revised in layers, and then the azimuth offset is added to or subtracted from the azimuth pulse count by the sign bit information of the original data of the target to obtain the correction azimuth; and the mean of correction azimuths of multiple responses is calculated to obtain a secondary radar plot azimuth. In the complex electromagnetic wave environment, the method can use the multiple judgment criteria to timely and accurately determine whether the original data of the detection target are true and reasonable or not, without increasing the hardware cost but greatly improving the detection capability of the air target affected by various disturbances. And according to the authenticity, the original data of the target is subjected to screening, normalized adjustment and cohesion, so as to improve the data quality of the detection target, and to enhance the reliability and stability of the target monitoring system.

The invention discloses a radar image clutter suppression method based on time-domain characteristics. According to the method, based on time-domain characteristics of a radar moving target, a dim target is detected, and great clutter information is suppressed. The method includes the steps such as background differentiation, clutter suppression, measurement information extraction and multi-target tracking. In the clutter suppression step, through measurement information output in the step of measurement information extraction and time-domain characteristics such as a target path output in the step of multi-target tracking, a target detection segmentation threshold is corrected. The method has the advantages that the defect that the traditional clutter suppression method performs threshold segmentation only by the aid of a gray level, clutter jamming is maximally suppressed on the basis of time-domain characteristics, and the method is applicable to detection and tracking of dim moving targets on the basis of PPI (plain position image) radar images.

The invention discloses a cadmium column reduction detection device for a full-automatic chemical analyzer, belonging to the technical field of biochemical equipment. The cadmium column reduction detection device is characterized in that a three-way valve is arranged between a sampling needle and a common connecting pipe; a three-way valve is arranged between a plunger pump and the common connecting pipe; a cadmium column is communicated with the two three-way valves; and a vacuum pump is respectively communicated with the sampling needle, a liquid path cleaning solution tank and a cadmium column cleaning solution tank through the three-way valves. The cadmium column reduction detection device has the beneficial effects that the full-automatic chemical analyzer can realize nitrate detection by adopting a cadmium column reduction method, the detection capacity of the chemical analyzer is improved, and the automatic detection process of the cadmium column reduction method is realized. The detection device has the advantages of simplicity in operation and accuracy in detection and is particularly suitable for detecting seawater, drinking water and other water with low nitrate content.

The invention discloses a vehicle-mounted radar target detection method and device based on double-threshold detection, and the method comprises the steps: S1, obtaining an echo signal of a target vehicle-mounted radar, carrying out the target detection through employing a first threshold, and obtaining a preliminary target detection result; S2, performing angle estimation on the preliminary target detection result detected in the step S1 to obtain an angle estimation result; S3, performing target detection on the angle estimation result obtained in the step S2 by using a second threshold which is greater than the first threshold, so as to obtain a final target detection result and output the final target detection result. The invention comprises a target preliminary detection module, an angle estimation module and a secondary target detection module. The invention has the advantages of being simple in implementation method, low in cost, good in weak target detection performance, low in omission ratio, small in calculated amount, high in detection efficiency and the like.

The invention discloses a man-machine hybrid enhanced small target detection and tracking method and system, and the method comprises the steps: positioning a target region, and obtaining a small target region image; extracting specific image information of the small target area image to obtain a small target detail image; constructing a small target detection and tracking model based on wearableequipment, designing and training a lightweight neural network target detection model, combining a context information technology and a Kalman filtering algorithm, and using a small target detail image to optimize the detection and tracking capability of a small target; circularly obtaining new image information by utilizing the steps to serve as a training set for enriching the small target detection and tracking model, and performing migration training on the small target detection and tracking model by utilizing the updated training set to obtain a small target detection and tracking enhancement model. The system comprises an acquisition and identification module, a sensor module, a detection and tracking module and a communication module. According to the invention, the accuracy of small target detection and tracking in the image is improved.

The invention relates to an automatic dual-exciting-coil conductor defect flaw detection device and a method. The device comprises a power trolley, a singlechip, a detection plate, exciting coils, giant magnetoresistance sensors and a relay, wherein the singlechip is arranged in the power trolley; the detection plate is arranged at one end of the bottom surface of the power trolley; two ends of the detection plate are respectively connected with the bottom surface of the power trolley elastically by springs; the relay is connected with the detection plate, and can control two sides of the detection plate to overturn downwards; the two exciting coils are fixed on the detection plate, and are symmetrically arranged on the detection plate, and are internally provided with the giant magnetoresistance sensors respectively; the bottom surfaces of the giant magnetoresistance sensors and the bottom ends of the exciting coils are at the same horizontal level; the giant magnetoresistance sensors are electrically connected with the singlechip. The dual-exciting-coil conductor automatic defect flaw detection device and the method effectively improve the capability of detecting the deep-layer defect and surface micro defect of the system, are high in detection accuracy and efficiency, and have popularization and using values.

The invention provides a remote sensing image small target detection method based on four-scale deep and shallow layer feature fusion. The method comprises the following steps: constructing a remote sensing image small target detection network structure based on four-scale deep and shallow layer feature fusion; training the network structure by adopting transfer learning to obtain a trained network structure; inputting a remote sensing data set into the trained network structure to obtain a target detection result of the remote sensing image: in the training process of the network structure, performing feature extraction on each layer of the input image by adopting VGG16, and fusing the extracted features of each layer by utilizing a feature fusion module to obtain four output feature layers; and inputting the output feature layer to a detection layer, and training the network structure by using an improved loss function to obtain a trained network. The method provided by the inventionhas the beneficial effects that the small target detection capability, speed, robustness and accuracy of the high-resolution remote sensing image are improved.

The invention discloses a spectrometer for an industrial field, and belongs to the technical field of spectrometers. The spectrometer comprises a light collecting and collimating module, an imaging module, a processing module, a control module and an interface extending and converting module, wherein the light collecting and collimating module is used for collecting target reflected light, collimating and splitting the collected light and outputting the processed light; a CCD drive circuit in the imaging module is used for controlling a CCD detector to acquire spectrum obtained after the light is processed by the light collecting and collimating module, the processing module is used for processing and displaying spectrum data acquired by the CCD detector, and comprises a signal conditioning unit, a data acquiring unit and a power supply unit, the control module is used for sending control signals to the processing module and the CCD drive circuit, and the interface extending and converting module is used for extending the interface of the spectrometer. An electricity leakage switch is additionally arranged, so that the spectrometer is safer and more reliable to work, and perfect combination of high energy utilization rate and high resolution is realized.

The invention discloses an XSS attack detection method, apparatus and device, and a medium. The method comprises the steps of obtaining to-be-detected traffic; extracting a payload in the to-be-detected flow to obtain a to-be-detected payload; performing corresponding processing on the to-be-detected payload by using a bypassing reduction strategy corresponding to the target bypassing strategy so as to reduce the payload subjected to bypassing deformation in the to-be-detected payload to obtain a corresponding processed payload; and determining whether the to-be-detected traffic is the XSS aggressive traffic or not based on the feature information of the processed payload. According to the method, before whether the to-be-detected traffic is the XSS aggressive traffic is determined based on the feature information of the payload, the to-be-detected payload is correspondingly processed by using the bypassing restoration strategy, so that the payload subjected to bypassing deformation in the to-be-detected payload can be restored, the missing report rate is reduced, and the detection capability aiming at the XSS attack is improved.

The invention relates to a method for determining nickel, chromium, silicon, manganese and phosphor in nickel-containing pig iron. The method is characterized in that five iron samples are taken in each batch of material, one spot is drilled on each iron sample, the drilled iron scraps are ground and pass through a 60-80-mesh target standard sieve; 10 ml of distilled water, 5 ml of concentrated nitric acid (65%) and 5 ml of concentrated hydrochloric acid (37%) are added in order in a 100 ml volumetric flask filled with 0.5000 g of the iron scrap sample for solving the sample, insoluble carbide is filtered and volume is metered to 100 ml; 0.4000 g of a pure iron matrix is added in a standard series solution; an inductively coupled plasma atomic emission spectrometry is used for determining the content of the elements of Ni, Cr, Si, Mn and P in the nickel-containing pig iron for analysis, an optimal analytical line for each element can be selected; spectrum interference of each coexisted element to the analytical line is inspected, and correction of an interference line in the analytical line can be carried out. The method is capable of shortening analysis period, mitigating labor intensity, increasing control capability and detection capability of the analysis result, reducing an application amount of a chemical reagent, reducing the waste liquid discharge, and reducing the analysis cost.

The invention relates to the field of shadow elimination in image processing, and provides a method for removing a shadow of a single image based on semi-supervised edge attention. The method comprises a generator and a discriminator, wherein the generator is divided into a shadow detection network, an edge attention module and a shadow elimination network. Through the training of the semi-supervised learning network, the shadow region of the shadow image of the complex scene can be detected, the shadow image is guided to perform shadow elimination, and a better shadow-eliminated image is obtained.

The embodiment of the invention discloses a counterfeit domain name detection method and device, electronic equipment and a storage medium, and relates to the technical field of network security detection. The counterfeit domain name detection method comprises the steps of obtaining a to-be-detected domain name; judging whether the domain name to be detected exists in a counterfeit domain name setor not by using a Bloom filter, wherein the counterfeit domain name set is generated on the basis of a domain name white list according to a counterfeit domain name generation mode; and if the domainname to be detected exists in a counterfeit domain name set, judging that the domain name to be detected is a counterfeit domain name. The embodiment of the invention has the capability of preventinga new counterfeit domain name attack, improves the detection capability, and greatly improves the detection efficiency by using the Bloom filter.

The invention discloses a vector network system for testing power transmission line passive interference. According to the system, a transmitting circuit is connected with a vector network analyzer sothat the vector network analyzer and a receiving circuit can be connected; the transmitting circuit comprises a transmitting antenna, an amplifier, a first port photoelectric conversion module, a first port connection optical fiber and a first port electro-optical conversion module which are connected in turn; the amplifier and the first port photoelectric conversion module are arranged in a first shielding box; the first port electro-optical conversion module inputs signals to the vector network analyzer; the receiving circuit comprises a receiving antenna, a second port photoelectric conversion module, a second port connection optical fiber and a second port electro-optical conversion module which are connected in turn; the second port photoelectric conversion module is arranged in a second shielding box; and the second port electro-optical conversion module receives the output signals of the vector network analyzer.

The invention discloses application of mussel GST alpha subtype gene in detecting a malachite green-polluting aquatic product, in particular to application of a reagent for detecting a transcriptionallevel of the mussel GST alpha subtype gene in detecting the malachite green-polluting aquatic product. A sequence of the mussel GST alpha subtype gene is as shown by SEQ ID No. 9. The reagent is a specific probe for the mussel GST alpha subtype gene or a specific primer for the mussel GST alpha subtype gene. By adopting the application of the invention, a novel detection method with higher sensitivity is provided for the polluted aquatic product and particularly for the malachite green-polluted mussel, and the food safety detection capacity is effectively improved.

The invention relates to the field of environmental perception of mobile robots, in particular to a hierarchical feature fusion method for multi-target detection of a mobile robot, and aims to improvethe detection capability of a target detection algorithm for targets of different scales so as to improve the environmental perception capability of an intelligent robot. The method includes: inputting the images in the data set into a pre-trained improved VGG-16, and preliminarily obtaining a feature map; respectively inputting the preliminarily acquired feature maps into a cavity convolution pyramid structure which comprises three cavity convolution integral branches with different expansion rates and is used for matching targets with different scales acquired by a visual sensor when the robot moves; fusing the feature maps acquired by different branches in a layered superposition mode provided by the invention, so that all channels in the feature maps contain feature information of different scales; gradually convolution is carried out on the fused feature maps to obtain feature maps of different sizes; and finally, obtaining the category and the bounding box of the to-be-detectedobject.

The invention discloses an ICT. The ICT comprises a floor, an electrical element pin testing mechanism, an electrolytic capacitor reverse plugging testing mechanism and a needle base reverse pluggingtesting mechanism, wherein the floor is driven to move towards an element side of a circuit board, the electrical element pin testing mechanism is arranged on the floor and used for testing whether ornot electrical elements, located on the element side, of pins can be normally used, the electrolytic capacitor reverse plugging testing mechanism is arranged on the floor and used for testing whetheror not an electrolytic capacitor on the element side is plugged reversely, and the needle base reverse plugging testing mechanism is arranged on the floor and used for testing whether or not a to-be-tested needle base on the element side is plugged reversely. By arranging the electrical element pin testing mechanism, the electrolytic capacitor reverse plugging testing mechanism and the needle base reverse plugging testing mechanism on the floor simultaneously, the technical problems in the prior art are solved that a floor testing function of an ICT is monotonous, comprehensive checking on electrical elements on the element side of the circuit board is lacked, and whether or not different electrical elements located on the element side of the circuit board are plugged reversely cannot bechecked simultaneously.

The invention discloses a method for detecting intermittent faults of a high-speed train closed-loop brake braking system, and particularly relates to the technical field of fault diagnosis. The defect that an existing high-speed train fault detection technology cannot effectively detect the intermittent faults with small amplitudes and limited duration is overcome. The method comprises the steps:continuously collected sample data under the normal working condition of a plurality of sensors of the high-speed train closed-loop brake braking system are discretely trained, on the basis of obtaining the direction and the fault amplitude lower bound of the intermittent faults of the high-speed train closed-loop brake braking system, flag values of statistical magnitudes of T2, Q, phi and D arecalculated correspondingly, and the statistical magnitude with the largest flag value is selected to conduct fault detection at the online stage.

The invention provides a category confirmation method and device for ground identifiers and a vehicle, and relates to the technical field of computers. The method comprises the following steps: acquiring an image comprising a to-be-determined ground identifier; performing inverse perspective transformation on the image to obtain a top view corresponding to the image; and determining the category of the to-be-determined ground identifier by using the top views and a ground identifier identification model, training the ground identifier identification model by using a top view set, and obtaining each top view in the top view set by performing inverse perspective transformation on an image comprising a ground identifier with a known category. By using the method provided by the invention, the detection capability of the ground identifier is improved, and especially the detection capability of the far-end ground identifier is improved, so that better technical support is provided for path planning, real-time decision making and driving control in the subsequent automatic driving process, and the method has relatively high practicability.

The invention discloses a training method of a generative adversarial multi-relation graph network model for detecting a machine account, and the training method comprises the steps: modeling a platform into a graph containing a node v and a relation r, and the number of the graph is determined by the type number of the relation r; generating a false target node vt of the source node v by using a generator G; respectively inputting the sampled node pairs (v, u) and (v, vt) into a connection relation discriminator D, and repeatedly training the connection relation discriminator D; reasoning node pairs in the graph by using the trained connection relation discriminator D, determining the connection relation of the node pairs, and further updating the structure of the graph; and inputting the representation vectors of the nodes into a classifier, updating parameters of the model according to a loss function and back propagation, and carrying out multiple times of training to obtain a trained generative adversarial multi-relational graph network model. The invention also discloses a machine account detection method based on the generative adversarial multi-relation graph network model.

The invention discloses a traffic sign identification method. The identification method comprises the steps of obtaining a to-be-identified image; preprocessing the to-be-identified image and generating an image pyramid; respectively extracting edge features and texture features of each layer of image in the image pyramid; performing feature association fusion on the edge features and the texturefeatures to obtain traffic sign information in the to-be-identified image; and performing identification processing based on the traffic sign information and a traffic sign classifier to obtain a traffic sign category corresponding to the traffic sign information. The invention further discloses a traffic sign recognition device and equipment and a storage medium. According to the invention, the position and size of the traffic sign can be better detected, and the detection capability of the traffic sign area is improved; and the recognition speed and the recognition rate can be improved.

The invention relates to a rapid and high-throughput plasmodium detection method. According to the method disclosed by the invention, two powerful molecular biological technologies of polymerase chain reaction (PCR) and micro-array are integrated, a PCR hybridization probe is directly fixed in a hybridization cabin and arranged on the same chip as a PCR reaction chamber; the detection method comprises the steps of blood sample DNA liquid extraction, PCR amplification, hybridization, washing and result analysis. The rapid and high-throughput plasmodium detection method disclosed by the invention can be used for rapid sensitive detection of falciparum malaria plasmodium, vivax malaria plasmodium and quartan malaria plasmodium, the detection efficiency of front-line inspection and quarantine personnel at import-export ports is greatly improved, not only is the workload reduced but also the problem of positive undetected samples possibly missed according to the conventional detection methods can be solved to the largest extent, and therefore the occurrence of plasmodium epidemic situation is prevented to the largest extent.