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37results about How to "Reduce the false alarm rate of detection" patented technology

Adaptive fault detection method for airplane rotation actuator driving device based on deep learning

The invention discloses an adaptive fault detection method for an airplane rotation actuator driving device based on deep learning. According to the invention, adaptive fault detection is carried out on the airplane rotation actuator driving device based on a sparse Dropout automatic coder and a noise reduction automatic coder and deep learning of Logistic regression, feature self-learning of original data is realized through using the Dropout automatic coder in a first layer and a layered noise reduction automatic coder model in a second layer and a third layer by adopting a multi-layer neural network based deep learning autonomous cognitive method, data features acquired by learning are inputted to a Logistic regression model so as to judge an operating state of the rotation actuator driving device, a threshold is enabled to change along with different inputs and different states of the system through additionally arranging an adaptive threshold fault observer, and a residual error caused by non faults is eliminated. The method disclosed by the invention can be effectively applied to fault diagnosis of the airplane rotation actuator driving device.
Owner:BEIHANG UNIV

Unmanned aerial vehicle video small-object detecting method based on super-resolution reconstruction

The invention discloses an unmanned aerial vehicle video small-object detecting method based on super-resolution reconstruction. The unmanned aerial vehicle video small-object detecting method comprises the steps of selecting one input image as a reference frame, and selecting three consecutive image frames for performing sub-pixel displacement estimation on the reference frame; then placing the displacement estimation result of the four image frames into a high-resolution image grid; and estimating pixels which are lost in the high-resolution image grid, thereby obtaining an objective image with a relatively high resolution. Afterwards, an objective template is extracted from the objective image, and the characteristic of the objective image is calculated. Then the reconstructed objective image is divided for obtaining a plurality of objective area blocks. Characteristic extraction and characteristic identification are successively performed on all objective area blocks, thereby finishing preliminary detection for the object. Afterwards, false object elimination is performed, thereby obtaining a final detection result.
Owner:XIDIAN UNIV

Ultraviolet image based water surface oil spill detection system and method

The invention discloses an ultraviolet image based water surface oil spill detection system and method and relates to the field of signal processing. The ultraviolet image based water surface oil spill detection system comprises an ultraviolet imaging module, a video decoding buffer module, an image processing module and an alarm module which are connected in sequence. The ultraviolet imaging module comprises an ultraviolet light source, an ultraviolet bandpass filter and a camera. The video decoding buffer module comprises a video decoding chip and a synchronous dynamic random access memory. The camera is connected to the video decoding chip and the video decoding chip is connected to the synchronous dynamic random access memory. The image processing module comprises a DSP (Digital Signal Processor) chip and a program loading chip. The video decoding chip, the synchronous dynamic random access memory and the program loading chip are all connected to the DSP chip. The alarm module comprises a relay, a sound and light alarm and a wireless data transmitter. The ultraviolet image based water surface oil spill detection system and method is good in water surface oil spill detection effect and high in anti-interference capability.
Owner:西安雷谱汇智科技有限公司

Course error correctingmethod and apparatus and magnetic field detection method and apparatus

The invention provides a course error correcting method. The course error correcting method comprises the following steps: (a) collecting magnetic field measurement data, gyroscope measurement data and accelerometer measurement data; (b) calculating detection statistics; (c) determining whether a magnetic field is in a stable state or not in a corresponding time interval between an s step and a (s+m-1) step of a person; and (d) if the magnetic field is in the stable state, adopting a magnetic field solved course as an observation amount, estimating a course angle error by utilizing Kalman filtering, and correcting the course of the person by utilizing the course angle error. The invention also provides a course error correcting apparatus. The course error correcting apparatus comprises an accelerometer, a gyroscope, a magnetometer, a signal acquisition unit and a signal processing unit. The invention also provides a magnetic field detection method and apparatus.
Owner:湖南云箭格纳微信息科技有限公司

Local gradient trilateral-based multi-scale infrared weak and small target detection method for graph domain

The invention discloses a local gradient trilateral-based multi-scale infrared weak and small target detection method for a graph domain. The method comprises the steps of converting an infrared image containing a weak and small target into a local gradient trilateral graph signal taking a node and an edge weight relationship as an expression mode; secondly, performing multi-scale decomposition on the local gradient trilateral graph signal according to multi-scale transform of a graph Laplacian matrix to obtain low and high-frequency sub-bands of the graph signal under different scales; thirdly, performing local weighting on the high-frequency sub-band of each scale according to the edge weight relationship of the graph signal, taking a mid-value as a new center node coefficient, and performing multiplicative fusion on the high-frequency sub-bands subjected to the local weighting; and finally, performing adaptive threshold segmentation on the high-frequency sub-bands subjected to the multiplicative fusion, determining a target space position, and outputting a detection result.
Owner:XIDIAN UNIV

POLSAR image marine target detection method based on polarization direction angle compensation

ActiveCN104318572AEasy to detectEliminate reflection symmetry issuesImage enhancementImage analysisSea wavesClassical mechanics
The invention discloses a POLSAR image marine target detection method based on polarization direction angle compensation. According to the method, the polarization scattering property of an artificial metal marine target is used for detection, and in order to solve the problem that sea clutter reflection symmetry is affected by direction angle deviation generated by sea wave disturbance, direction angle compensation is conducted on a POLSAR image, and the detection accuracy of the marine target is improved. The method includes the steps that firstly, a completely-polarized image is acquired and related preprocessing operation is conducted; then, the polarized direction angle is calculated through a coherence matrix and direction angle compensation is conducted on the coherence matrix; finally, the intensity value of an element T'13 in the coherence matrix obtained after direction angle compensation is extracted and the artificial metal marine target is detected. The method overcomes the defects that a common marine target detection algorithm is complex in theory, difficult to achieve, poor in robustness and the like, and meanwhile starting from the polarization scattering property of the target, the marine target is accurately separated from sea clutters and target side lobes. The detection method is visual in principle, simple in algorithm and capable of facilitating programming realization and expansion.
Owner:CENT SOUTH UNIV

Multi-camera complex scene self-adaptive vehicle collision early-warning device and early-warning method

The invention provides a multi-camera complex scene self-adaptive vehicle collision early-warning device and method. The multi-camera complex scene self-adaptive vehicle collision early-warning deviceis characterized in that a multi-camera sensing module includes three fixed focus cameras whose focal lengths are sequentially reduced, and the multi-camera sensing module transmits the detected front image information to a data processing and calculation module; the data processing and calculation module performs vehicle detection, vehicle tracking, and front and rear distance calculation on theimage information according to a set built-in collision warning method, and generates collision early-warning information; and a collision warning module receives the collision early-warning information, and generates warning information to a driver for warning prompt. As the three fixed focus cameras of the multi-camera complex scene self-adaptive vehicle collision early-warning device cover thewide detection range, and also avoid the problems of high cost and large size caused by using a zoom camera. The multi-camera complex scene self-adaptive vehicle collision early-warning method performs scene classification on classifiers to enable the cascade classifiers to be small in volume, high in detection efficiency, and more highlighted in vehicle features in the corresponding scene, so that the complex scene adaptive ability of the system is high.
Owner:HEFEI UNIV

Nonlinear node detector of frequency modulation continuous wave system

The invention provides a nonlinear node detector of a frequency modulation continuous wave system. The nonlinear node detector comprises a modulation signal generator used for generating modulation signals, a voltage-controlled oscillator controlled by the modulation signals to generate continuous wave frequency modulation signals, a frequency multiplier used for multiplying the continuous wave frequency modulation signals, a first amplifier used for amplifying the continuous wave frequency modulation signals, a transmitting antenna, a receiving antenna used for receiving echo signals, a second amplifier used for amplifying the echo signals, a mixer utilizing the multiplied continuous wave frequency modulation signals as local oscillator signals and mixing the amplified echo signals with the local oscillator signals to generate beat signals, a filter used for filtering the beat signals, a third amplifier used for amplifying the filtered beat signals and a digital signal processing terminal used for processing the beat signals, analyzing frequency and size of the beat signals, determining whether an electronic target exists in a detection area or not and calculating the distance between the electronic target and the detector. The nonlinear node detector can effectively avoid electromagnetic wave interference signals in environment background, improves detection performance of the electronic target and reduces false alarm rate.
Owner:NO 50 RES INST OF CHINA ELECTRONICS TECH GRP

Target detection method, device and equipment, computer equipment and storage medium

ActiveCN109903272ASuppression of background distractorsAccurate locationImage enhancementImage analysisPattern recognitionProcess variance
The invention relates to a target detection method, device and equipment, computer equipment and a storage medium. The method comprises the following steps: obtaining a target image, and carrying outvariance weighted local entropy processing on the target image to obtain a variance weighted local entropy image of the target image; Further performing binarization processing and clustering analysison the variance weighted local entropy image to obtain a processed variance weighted local entropy image; Obtaining a fusion image according to the processed variance weighted local entropy image andthe local contrast enhancement image of the target image; And analyzing the fused image to determine a target in the target image. By the adoption of the method, background interferents in the improved local contrast image are restrained, the accurate position of the infrared weak small target is obtained, and the detection false alarm rate is greatly reduced.
Owner:TIANWEI ELECTRONICS SYST ENG

Crossing bridge and offshore ship joint detection method in onboard remote sensing image

The invention relates to a crossing bridge and offshore ship joint detection method in an onboard remote sensing image. The crossing bridge and offshore ship joint detection method comprises the steps of firstly, carrying out otsu self-adaptation threshold segmentation on the onboard remote sensing image, then sequentially carrying out morphology closed operation and morphology open operation on a segmentation result image, obtaining a water body district image, then carrying out binaryzation operation on the water body district image, obtaining a water body district binary image, separating target candidate districts and water body background districts, calculating the area average value of the target candidate districts, checking whether the water body background districts exist around the target candidate district or not, if the value of the area of one target candidate area is larger than the average value and is surrounded by the water body background districts, determining that the target is an offshore ship, and if the value of the area of one target candidate district is smaller than the average value and only two opposite sides of the target candidate district are the water body background districts, determining that the target is a crossing bridge. The crossing bridge and offshore ship joint detection method is high in calculating efficiency, real-time processing can be easily carried out on an onboard computer, and the detection false alarm rate is low.
Owner:NORTHWESTERN POLYTECHNICAL UNIV

Ultraviolet biological chip integrated sensor

The invention provides an ultraviolet biological chip integrated sensor, and relates to the field of design and manufacturing of biological warfare agent sensors. In the field, all light sources of the conventional LIF detection systems generate ultraviolet light by frequency multiplication of impulsive visible or infrared light; the conventional LIF detection system has the defects of high price, low efficiency, large volume and crispness, and is inconvenient for real-time detection and outdoor use; and the impulsive ultraviolet light is low in duty ratio, and has low detection sensitivity to biological suspended particles, and the light intensity of the conventional continuous ultraviolet light is not high enough to excite the biological suspended particles to fluoresce; and all these problems are great obstacles in the application of the detection system. The ultraviolet biological chip integrated sensor of the invention uses multi-wavelength ultraviolet LEDs as excitation light sources and overcomes the defects of the conventional light source; the multi-wavelength ultraviolet LEDs, an Si-PIN detector and an ultraviolet filter plate are integrated on the same substrate, so that the sensor has the capability of detecting and identifying various biological warfare agents and can meet the light, firm, quick-response and high-sensitivity use requirements of the field environmental on the detector while improving the detection efficiency and lowering a detection false alarm rate.
Owner:CHANGCHUN UNIV OF SCI & TECH

Synthetic aperture radar (SAR) target detection false alarm elimination method based on priori scene knowledge

The invention discloses a synthetic aperture radar (SAR) target detection false alarm elimination method based on priori scene knowledge, wherein the SAR target detection false alarm elimination method mainly settles a problem of large number of SAR image target detection false alarms in a complex scene. The SAR target detection false alarm elimination method comprises the following steps of (1) inputting an original SAR image, performing down-sampling twice and mean filtering on the original SAR image; (2) performing area growth on the SAR image after preprocessing, eliminating an object-sized communicating area which are not grown out, and using the rest non-grown-out communicating area as the area to be classified; (3) selecting a training sample, performing classification on the area to be classified, and obtaining an area in which an object impossibly exists; and (4) eliminating the false alarm that is detected in the area in which the object impossibly exists, and obtaining a result image. The SAR target detection false alarm elimination method can effectively reduce detection of false alarm in the complex scene and can be used for afterprocessing in detection of the SAR image target.
Owner:XIDIAN UNIV

Remote sensing image riverway target detection method and device based on feature fusion

The invention relates to a remote sensing image riverway target detection method and device based on feature fusion, and a computer readable storage medium. The method comprises steps of a remote sensing image containing a riverway being collected and inputted; performing enhancement preprocessing on the remote sensing image by using a multi-scale contrast improvement method; shear wave transformation being carried out on the image after enhancement preprocessing to obtain variance maximum shear wave feature maps of different scales and directions; extracting an SUSAN edge feature map from theimage after enhancement preprocessing by using a similarity comparison method; calculating information entropies of the shear wave feature map and the SUSAN edge feature map, and obtaining a featurefusion map by using an information entropy weighting method; and performing threshold segmentation and morphological operation on the feature fusion image to obtain a final river target detection result image. According to the method, the capability of river channel detection under the remote sensing image is improved, and problems of low precision and high false alarm rate of traditional river channel detection are avoided.
Owner:BEIJING INST OF ENVIRONMENTAL FEATURES

An Adaptive Fault Detection Method for Aircraft Rotary Actuator Drives Based on Deep Learning

The invention discloses an adaptive fault detection method for an airplane rotation actuator driving device based on deep learning. According to the invention, adaptive fault detection is carried out on the airplane rotation actuator driving device based on a sparse Dropout automatic coder and a noise reduction automatic coder and deep learning of Logistic regression, feature self-learning of original data is realized through using the Dropout automatic coder in a first layer and a layered noise reduction automatic coder model in a second layer and a third layer by adopting a multi-layer neural network based deep learning autonomous cognitive method, data features acquired by learning are inputted to a Logistic regression model so as to judge an operating state of the rotation actuator driving device, a threshold is enabled to change along with different inputs and different states of the system through additionally arranging an adaptive threshold fault observer, and a residual error caused by non faults is eliminated. The method disclosed by the invention can be effectively applied to fault diagnosis of the airplane rotation actuator driving device.
Owner:BEIHANG UNIV

A Fault Detection, Diagnosis and Performance Evaluation Method for Redundancy Aileron Actuator

The invention discloses a fault detection, diagnosis and performance evaluation method for a redundant aileron actuator. According to the method, fault detection, diagnosis, evaluation and real-time detection of the actuator are performed by means of an input order signal, an output displacement signal, a force motor current signal and aerodynamic loading data of the actuator; the fault detection is realized by a two-stage neural network, a first neural network is used as a system observer and is matched with actual output to acquire a residual error, and a second neural network outputs a self-adaptive threshold value synchronously; the fault detection is realized by the system observer and a force motor current observer; a time domain feature is extracted from a residual error signal and output to a self-organizing mapping neural network, and a minimum quantization error is acquired and normalized to a health degree, so that the actuator performance is evaluated; and on the basis of fault detection, the aerodynamic loading data is introduced, by means of a specific input order spectrum, the system observer and the neural network with the self-adaptive threshold value are trained, and the real-time fault detection is realized.
Owner:北京恒兴易康科技有限公司

A water surface oil spill detection system and method based on ultraviolet images

The invention discloses a water surface oil spill detection system and method based on ultraviolet images, and relates to the field of signal processing. Including sequentially connected ultraviolet imaging module, video decoding cache module, image processing module, alarm module; ultraviolet imaging module includes ultraviolet light source, ultraviolet bandpass filter and camera; video decoding cache module includes video decoding chip and synchronous dynamic random access memory , the camera is connected to the video decoding chip, and the video decoding chip is connected to the synchronous DRAM; the image processing module includes a DSP chip and a program loading chip, and the video decoding chip, the synchronous dynamic random access memory, and the program loading chip are all connected to the DSP chip; the alarm module includes The relay, the sound and light alarm and the wireless data transmitter, the DSP chip is connected with the sound and light alarm through the relay, and the DSP chip is connected with the wireless data transmitter through the network interface. The invention has good detection effect on water surface oil spill and strong anti-interference ability.
Owner:西安雷谱汇智科技有限公司

Infrared small target detection method based on template filter and false alarm suppression in cloud background

The invention discloses an infrared small target detection method based on template filtering and false alarm suppression under cloud background. First, the image is subjected to maximum median filtering to remove significant noise to complete image preprocessing. Secondly, Robinson template filtering is used to suppress the background and highlight the target. , and then divide the original image into cloud areas. In the cloud area, the Robinson filtered result is binarized using a low threshold, while in the non-cloud area, a high threshold is used. Finally, the binarized result is further eliminated. Multiple "pseudo target points" generated by the same target are used to complete "coarse detection"; adjacent frame images that have been processed in the spatial domain continue to be processed by time domain operations to complete "fine detection", thereby realizing the detection of small infrared targets. The present invention adds a constant false alarm suppression algorithm to the inter-frame track correlation, which greatly reduces the detection false alarm rate.
Owner:NANJING UNIV OF SCI & TECH

Multi-camera complex scene adaptive vehicle collision warning device and warning method

The invention provides a multi-camera complex scene self-adaptive vehicle collision early-warning device and method. The multi-camera complex scene self-adaptive vehicle collision early-warning deviceis characterized in that a multi-camera sensing module includes three fixed focus cameras whose focal lengths are sequentially reduced, and the multi-camera sensing module transmits the detected front image information to a data processing and calculation module; the data processing and calculation module performs vehicle detection, vehicle tracking, and front and rear distance calculation on theimage information according to a set built-in collision warning method, and generates collision early-warning information; and a collision warning module receives the collision early-warning information, and generates warning information to a driver for warning prompt. As the three fixed focus cameras of the multi-camera complex scene self-adaptive vehicle collision early-warning device cover thewide detection range, and also avoid the problems of high cost and large size caused by using a zoom camera. The multi-camera complex scene self-adaptive vehicle collision early-warning method performs scene classification on classifiers to enable the cascade classifiers to be small in volume, high in detection efficiency, and more highlighted in vehicle features in the corresponding scene, so that the complex scene adaptive ability of the system is high.
Owner:HEFEI UNIV

Method for detecting transmission towers based on synthetic aperture radar images

A method for detecting transmission towers based on synthetic aperture radar images is provided in that embodiment of the invention, By processing high resolution SAR (Synthetic Aperture Radar) images, the region of interest (ROI) is obtained and the semi-variance of the region is calculated. The transmission tower is detected by neural network. The invention does not require that the image must be a full polarimetric SAR image with high price, moreover, the invention can detect more transmission tower targets for the same SAR image, especially when the outline of the high-voltage transmissiontower on the image is not clear and there are many false targets, and the detection false alarm rate is lower than that of the prior art.
Owner:STATE GRID ECONOMIC TECH RES INST CO +1

Vehicle-mounted airport runway foreign object detection system and method

The invention provides a vehicle-mounted airport runway foreign object detection system, comprising: a vehicle, a vehicle-mounted millimeter-wave radar, a vehicle-mounted camera platform, video linkage monitoring equipment, and a display device; the vehicle-mounted millimeter-wave radar is used to detect foreign objects on the airport runway , and send an alarm message when a foreign object is found; the vehicle-mounted camera platform is used to obtain the original image of the foreign object according to the alarm information; the video linkage monitoring equipment is used to display the foreign object through the display device according to the original image. The invention also provides a corresponding method. The invention adopts a vehicle-mounted multi-sensor method to realize the detection of foreign objects on an airport runway, which can effectively guarantee the detection performance of the system. The system uses high-resolution imaging radar to detect foreign objects on the airport runway, effectively ensuring the system's detection performance in dark nights and rainy weather environments. The system adopts the radar detection and positioning video linkage monitoring method to effectively reduce the false alarm rate of detection and improve the operability of the removal of foreign objects on the airport runway.
Owner:NO 50 RES INST OF CHINA ELECTRONICS TECH GRP

Hyperspectral remote sensing small target detection method based on multiple aperture information processing

ActiveCN103293523BImprove the immunityStrong anti-spectral aliasing interference abilityWave based measurement systemsInformation processingData acquisition
The invention discloses a hyperspectral remote sensing small target detection method based on multiple aperture information processing. The hyperspectral remote sensing small target detection method based on the multiple aperture information processing comprises data observation, information processing and target detection. In the data observation, distributed parallel partitioned information processing performed on hyperspectral remote sensing data through a multiple aperture asynchronous mapping mechanism is simulated, partitioned data collection is performed on the hyperspectral remote sensing through a data collection chip, multiple aperture information obtaining through a fly visual system and a mapping mechanism are simulated, and the hyperspectral remote sensing spectrum data is decomposed and recombined according to an ommatidium mapping function to form into a spectrum data cube which is about local ground objects and construct a distributed parallel partitioned information processing mode. In the information processing, a cartridge system of the fly visual system is simulated to achieve integration of redundant compression and super sensitivity. In the object detection, a self-adaption mechanism of optic high order nerve cells of the fly visual system is simulated and an anomaly detection result is obtained through a self-adaption small target detection algorithm in combination with judgment of whole situation anomaly and local anomaly.
Owner:HOHAI UNIV CHANGZHOU

Low-altitude sound target comprehensive identification method and device based on multi-dimensional feature space

PendingCN111968671AUnique propeller power structureHigh strengthSpeech recognitionSensor arrayFeature vector
The invention relates to a low-altitude sound target comprehensive identification method and device based on a multi-dimensional feature space. Signals are collected through a multi-channel sound sensor array; the acquired signals are analyzed and calculated to obtain a multi-dimensional feature vector including time-frequency features, spatial features and harmonic features; and the multi-dimensional feature vector is inputted into a target classification model to carry out target identification. The method can effectively improve the target identification rate.
Owner:THE THIRD RES INST OF CHINA ELECTRONICS TECH GRP CORP

Maritime target detection method for polsar images based on polarization direction angle compensation

ActiveCN104318572BEasy to detectEliminate reflection symmetry issuesImage enhancementImage analysisSea wavesClassical mechanics
The invention discloses a POLSAR image marine target detection method based on polarization direction angle compensation. According to the method, the polarization scattering property of an artificial metal marine target is used for detection, and in order to solve the problem that sea clutter reflection symmetry is affected by direction angle deviation generated by sea wave disturbance, direction angle compensation is conducted on a POLSAR image, and the detection accuracy of the marine target is improved. The method includes the steps that firstly, a completely-polarized image is acquired and related preprocessing operation is conducted; then, the polarized direction angle is calculated through a coherence matrix and direction angle compensation is conducted on the coherence matrix; finally, the intensity value of an element T'13 in the coherence matrix obtained after direction angle compensation is extracted and the artificial metal marine target is detected. The method overcomes the defects that a common marine target detection algorithm is complex in theory, difficult to achieve, poor in robustness and the like, and meanwhile starting from the polarization scattering property of the target, the marine target is accurately separated from sea clutters and target side lobes. The detection method is visual in principle, simple in algorithm and capable of facilitating programming realization and expansion.
Owner:CENT SOUTH UNIV

An on-orbit detection and recognition device and method applied to remote sensing images

An on-orbit detection and identification device and method applied to remote sensing images, including a main control unit, a storage unit, a processing unit, a switching unit, an IO unit, and a power supply unit; Extraction, the extracted image data is extracted based on morphology for suspicious targets, and target slices are obtained according to the suspicious target extraction results, and the slices are sent to the switching unit; the switching unit distributes the sliced ​​data to the The processing unit completes the deep learning processing based on the convolutional neural network, and classifies and stores the target slices. The storage unit sends the stored packaged data to the IO unit and outputs it according to the data output instruction of the main control unit.
Owner:BEIJING INST OF SPACECRAFT SYST ENG

A three-dimensional moving target detection method and system

An embodiment of the present invention provides a method and system for detecting a three-dimensional moving object, wherein the method includes: acquiring a three-dimensional range image of a multi-view scene to be processed, where the three-dimensional range image includes a three-dimensional moving target; extracting a three-dimensional distance of the multi-view scene The local invariant feature information of the image, and determine the feature description vector of the local invariant feature information; register the 3D range image of the multi-view scene according to the local invariant feature information and feature description vector; according to the registered multi-view scene The local invariant feature information of the 3D range image is used to determine the candidate detection area; the candidate detection area is verified and reviewed by iterative ground estimation and elevation filtering to obtain the accurate detection area; the 3D moving target detection is performed on the accurate detection area. The embodiment of the present invention reduces the detection false alarm rate, improves the detection efficiency, reduces the amount of data processing, and obtains a more accurate detection effect through repeated iterations.
Owner:湖南峰华智能科技有限公司
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