13results about How to "Strong resolution" patented technology

The invention discloses an ionizing flexible pressure sensor with an adjustable linear interval and a preparation method thereof, and belongs to the technical field of pressure sensing. The sensor is composed of an upper PET substrate, a positive electrode, a TPU / ILs ionic membrane, a Gr / WPU sponge, a polyurethane sponge frame, a negative electrode and a lower PET substrate from top to bottom. The Gr / WPU sponge elastomer with adjustable conductivity is introduced on the basis of the ionization type pressure sensor with the sandwich structure, the double-electric-layer capacitance of the sensor is regulated and controlled by changing the resistance range of the Gr / WPU sponge elastomer, and the linear interval of the pressure sensor is adjustable in a wide range; the pressure sensor has good cycling stability, high response recovery speed and good resolution capability for small pressure in a wide pressure detection range, the detection range can reach 0-2300 kPa, the linearity is 0.98, the sensitivity is 1.11 kPa <-1 >, and the pressure sensor has good application prospects.

The invention belongs to the technical field of biology, and particularly relates to an SSR molecular marker primer group for identifying dracaena dracaena varieties and application of the SSR molecular marker primer group. The SSR molecular marker primer group totally contains 16 pairs of primers, the polymorphic information indexes (PIC) of the 16 pairs of primers are all greater than 0.6, the number of repetitive units is 3-5, and the number of repetitive times is 5-7. The SSR primer provided by the invention has the characteristics of high amplification efficiency, stable amplification result, good polymorphism, strong specificity and the like. By utilizing the SSR molecular marker primer group, not only can different dragon tree varieties and dragon tree species be identified, but also the dragon's blood raw material can be subjected to traceability detection. The method disclosed by the invention has important technical guidance significance for development and utilization of the dragon's blood medicinal material and breeding of fine dragon tree varieties.

The invention discloses a method for determining ethylene content in wheat by gas chromatography, and relates to the technical field of biological detection.The method is characterized by comprising the steps that a wheat grain sample is prepared and placed in a glass bottle with a plug under certain conditions, and gas to be detected is generated; extracting a to-be-detected gas sample from the glass bottle with the plug, and sequentially injecting the to-be-detected gas sample into the gas chromatograph to obtain the ethylene peak area of the to-be-detected gas; sequentially injecting the standard gas into a gas chromatograph, and drawing a calibration curve to obtain the ethylene peak area of the standard gas; and calculating the ratio of the ethylene peak area of the to-be-detected gas to the ethylene peak area of the standard gas to obtain the ethylene content in the to-be-detected gas sample. The determination method provided by the invention can realize detection with lower quantitation limit and wider linear range, and has the characteristics of high sensitivity, high flux, rapidness, convenience, accuracy and reliability, the detection time of one sample is only 1-2min, and the method is suitable for detecting the plant hormone ethylene in wheat grains and seedlings.

The invention discloses a ring main unit fault processing method and device, a storage medium and a program product, and belongs to the technical field of power distribution automation. The method comprises the following steps: deploying a current sensor, a voiceprint sensor, a vibration sensor and an arc light sensor in a ring main unit, and synchronously collecting an electrical signal, a sound signal, a vibration signal and an optical signal when a fault occurs; carrying out preprocessing and feature extraction on the collected multi-modal data to obtain multi-dimensional feature parameters such as current amplitude, spectrum features, vibration energy and light intensity features; and calculating fault confidence based on a weighted fusion algorithm, and outputting fault type and position information when the confidence exceeds a judgment threshold. By fusing electrical quantity and non-electrical quantity information, real fault and non-fault disturbance can be distinguished, atypical faults such as high-resistance grounding and arc faults can be accurately identified, the false alarm rate is reduced, the reliability and the intelligent level of a ring main unit protection system are improved, and the method is suitable for intelligent operation and maintenance scenes of an urban power distribution network.

The application provides an optical detection device for a deep-cavity optical fiber end face and a cleaning detection equipment, and belongs to the field of optical communication. The optical detection device comprises a light source barrel lens, an illumination turning unit, an imaging turning unit, a telescope lens group, a detection prism, an imaging barrel lens, an imaging unit and a focusing unit. The imaging turning unit is used for turning the image and expanding the space. The telescope lens group realizes long-distance image transmission in a narrow space. After the oblique outgoing illumination light of the detection prism is deflected, it is perpendicular to the surface to be detected, and the illumination is more uniform. The imaging barrel lens adopts an image-side telecentric design. The imaging unit adopts a no-interface Schmitt structure design, which can solve the shallow depth of field problem caused by high resolution and realize automatic focusing with the focusing unit. The overall structure of the application is simple and stable in imaging. The front-end integrated prism turning light path eliminates the perspective error, and the double light path design improves the detection efficiency. The application can be widely applied in the fields of optical communication, 3C, semiconductor and the like with deep-cavity scenes.

The application discloses a kind of fast moving face recognition method and system based on multi-frame image enhancement, comprising the following steps: through imaging device acquisition multi-frame image sequence, obtain multi-frame image after pre-processing;The multi-frame image after pre-processing is input into the improved MonST3R network, carries out spatial alignment and structure analysis, obtains the image after alignment and three-dimensional structure information;The above result is input into CRNet network, separates and enhances multi-scale feature, and obtains enhanced feature;Enhanced feature is input into space-time attention fusion module, and multi-frame feature representation is obtained by weighted fusion;Fusion feature is input into identification network, and dimension reduction is carried out, and face embedding feature vector is obtained;Similarity comparison is carried out between embedding feature and database template, and recognition result and confidence prompt are output.The application can realize efficient, accurate and resource-friendly face recognition under dynamic complex environment.

The invention relates to a device and method for evaluating the contact direction and contact force of a double-parameter sensor and a balloon catheter, and the double-parameter sensor comprises a central tube elastomer structure, a packaging material, a multimode optical fiber, and a nanometer silver powder reflection layer. The evaluation device comprises the double-parameter sensor, an optical power generation and data acquisition unit and a computer, and the evaluation method combines an array type optical fiber optical power signal with an LSTM neural network model, excavates the change characteristics of a light intensity signal in time, accurately measures and calculates the nonlinear strain and force borne by the elastomer in real time, and calculates the nonlinear strain and force of the elastomer in real time. Three-dimensional reconstruction is carried out according to the strain and force of the elastomer, and the pushing force and torque of the catheter are correspondingly adjusted directly according to the magnitude and direction of the contact force in the navigation or ablation process, so that the problem that the catheter blindly punctures the blood vessel wall in the navigation process or the pulmonary vein opening is insufficiently blocked in the balloon ablation process is solved, and the safety of an operation is ensured.

The invention provides a method for evaluating compound amoxicillin powder, which belongs to the technical field of medicine detection, and comprises the following steps: detecting the content of an effective component of a medicine, and recording the content as the content A of the effective component; enabling the medicine to sequentially pass through the simulated gastric acid environment and the simulated small intestine environment, detecting the active ingredient content of the medicine after passing through the simulated gastric acid environment, recording the active ingredient content as an active ingredient content B, and detecting the active ingredient content of the medicine after passing through the simulated small intestine environment, recording the active ingredient content as an active ingredient content C; and counting the content change of the effective components of the medicine, and evaluating the compound amoxicillin powder. According to the technical scheme provided by the invention, the purposes of simplifying the evaluation method and reducing the cost are achieved.

The present disclosure provides a method and system for identifying the source of mobile application screenshots based on deep learning, which relates to the field of artificial intelligence. The method includes two steps: data collection and model construction and training: the data collection step constructs a mobile application sample library; the model construction and training step includes four steps: step 1, improving the MobileNetV3 network and constructing the corresponding loss function to form an improved MobileNetV3‑Large network; step 2, using the set contrast loss function to train the kernel parameters to obtain a trained mobile application matching model; step 3, processing the pictures in the mobile application sample library; step 4, using the trained mobile application matching model, calculating the Euclidean distance between the specific feature and each feature in the mobile application feature library, and obtaining the minimum value of all Euclidean distances. If it is lower than the threshold, the corresponding mobile application name is returned, which can continuously realize the accurate recognition capability of the latest mobile applications.

This utility model provides a wide-angle optical system and its application camera lens, mainly composed of 7 lenses. The first lens has a convex object plane and a concave image plane, with negative optical power. The second lens has concave object plane and image plane, with negative optical power. The third lens has convex object plane and image plane, with positive optical power. The fourth lens has convex object plane and image plane, with positive optical power. The fifth lens has convex object plane and image plane, with positive optical power. The sixth lens has concave object plane and image plane, with negative optical power. The seventh lens has a convex object plane and a concave image plane, with positive optical power. The high-pixel machine vision recognition optical system configured in this application has the advantages of high pixel count, strong resolution, and ultra-wide-angle design. It has a compact structure, is easy to process and install, and further improves the imaging effect of the equipment paired with the system.

The invention discloses a DRF-Net-based small target detection method under a view angle of an unmanned aerial vehicle. Constructing an unmanned aerial vehicle aerial photography small target detection data set; a frequency domain guide feature enhancement module FCSA is introduced in the shallow layer stage of the backbone network; a multi-frequency reconstruction module MFRB is introduced in the high-level stage; constructing DRF-Neck in a neck structure, generating a saliency graph S based on MFRB output features, and introducing saliency-driven deformable convolution SAR-DCN, content aware recombination S-CARAFE and a dynamic feedback controller DFC to form a closed-loop optimization mechanism of saliency generation-self-routing convolution-dynamic feedback; and finally, the features are input into a decoupling detection head, network parameters are optimized through joint optimization of cross entropy loss and AHIoU loss, and a small target detection result in an unmanned aerial vehicle aerial photographing scene is output by using non-maximum suppression in a reasoning stage. Compared with the prior art, the method has the advantages that the detection precision on the unmanned aerial vehicle aerial small target data set is improved, and the method can be applied to the fields of unmanned aerial vehicle inspection, urban security monitoring, traffic target detection and the like.

This invention discloses an ultra-micro target imaging method and system. It receives the full-band reflected light field from an ultra-micro target illuminated by a full-band light source, performs high-frequency and low-frequency switching filtering on the reflected light, and collects the intensity information of the filtered reflected light. Fourier transform and wavelet transform are then performed on the intensity information to obtain global and local images. Global features of the global image are extracted, and local features of the local image are extracted. The global and local features are then fused, and an enhanced image of the ultra-micro target is obtained based on the fused features. This invention solves the technical problem of low imaging accuracy in existing ultra-micro target imaging systems, achieving ultra-high resolution, strong noise resistance, and fast imaging speed. It can effectively solve the chip imaging problem during eutectic bonding, and the entire system has a simple structure, low cost, and is easier to maintain.

The invention relates to the technical field of multi-layer composite material defect detection, in particular to an ultrahigh-resolution multi-layer structure interface layering ultrasonic detection method which comprises the following steps: constructing a multi-layer structure interface and a grid model thereof, setting each grid point as an acquisition point, acquiring an original echo signal of each acquisition point by configuring an excitation signal, and calculating the multi-layer structure interface layering ultrasonic detection method according to the original echo signal. Determining a reference signal and translation window parameters, applying a mobile translation window to the original echo signal of each acquisition point, calculating a correlation coefficient of the signal in the window and the reference signal to obtain a relationship between the correlation coefficient and a translation distance, and analyzing the correlation coefficient and the translation distance of each acquisition point to obtain a correlation coefficient of the reference signal; and extracting phase feature data of each acquisition point in combination with an analysis result, mapping the phase feature data to a corresponding spatial position of the grid model, and generating a layering defect detection image of the multilayer structure interface. According to the method, high-precision detection of the layering defect of the interface of the multilayer structure is realized by comprehensively utilizing signal processing and space mapping technologies.