25results about How to "Reduce resolution" patented technology

The application is suitable for the technical field of laser radar, and provides a laser radar, which comprises a light source, a transmitting module, a receiving module, a transmission module, a detecting module and a signal processing module; the transmission module comprises a first coupler and a plurality of transmission media, wherein the local oscillator beam is transmitted to at least one transmission medium for delay processing through the first coupler, and the delay amount of the at least one transmission medium is different from that of the other transmission media; the detecting module is connected with the transmission module and the receiving module respectively, is used for receiving the echo signal and the delayed local oscillator beam output by the transmission module, performing beat frequency processing on the echo signal and the delayed local oscillator beam to obtain a beat frequency signal, and converting the beat frequency signal into a detecting electric signal; and the signal processing module is electrically connected with the detecting module, is used for determining a to-be-measured object according to the detecting electric signal. The laser radar provided by the application can improve the strength of the detection signal in long-distance measurement.

The application provides a method for converting a 32-bit face depth map into an 8-bit depth map for live body detection, and the method comprises the following steps: S1, collecting a TOF near-infrared image and a depth map; and processing the 8-bit near-infrared image through S2 and the 32-bit depth map through S4; S2, performing face detection on the near-infrared image; S3, expanding the face detection frame; S4, converting the 32-bit depth map into an 8-bit depth map; and S5, performing face frame cropping. According to the method, the pixel information of the face in the 32-bit depth map can be obtained through face detection on the original 8-bit near-infrared image and the position of the face frame, the pixels of the face are reserved by operating the pixels, the 8-bit depth map of the face is finally converted, the important pixel information is not lost in the depth map, and the color depth difference is maximized.

This invention discloses a time amplifier with self-cancelling quantization noise and a fractional-frequency division phase-locked loop (PLL), belonging to the field of frequency synthesis technology. The self-cancelling quantization noise time amplifier of this invention is based on a resistor-discharge type time amplifier. A control signal containing quantization error information is output through a slow-slope control signal generator to control the slow-discharge path of the time amplifier. This achieves K-fold time error amplification while simultaneously canceling fractional-frequency division quantization noise. The PLL architecture built based on this amplifier eliminates the need for a large-delay loop digital-to-time converter. The phase noise of the slow-slope control signal generator is suppressed by the time amplification gain, breaking the performance trade-off of traditional architectures. This invention achieves a low-noise, low-power, and high-linearity fractional-frequency division PLL design without degrading the performance of the time amplification phase detector.

The application belongs to the technical field of image processing, and relates to a light field microscopic image processing method based on a microlens array. The application establishes an optical path model of a light field microscope imaging system based on the microlens array; according to size data of a target microscope, the microlens array is designed, and all parameters of the optical path model are determined; according to optical parameters of the optical path model, various parameters required for high-resolution image reconstruction are designed; the microlens array is manufactured according to the determined microlens array parameters; the manufactured microlens array is integrated into a traditional microscope to assemble the light field microscope; the assembled light field microscope is used to collect an image array, the image array is divided into multiple sub-images, and fusion processing is performed to obtain a final target image. Without improving the hardware complexity, the application significantly enhances the contrast and definition of the image, and effectively solves the technical problems of low spatial resolution and low signal-to-noise ratio of the existing light field microscope.

This invention discloses a method, apparatus, and product for detecting small targets in drone aerial photography, relating to the field of computer vision, to improve the detection performance and parameter efficiency of small targets in complex background scenes. In the visual feature extraction process, the aerial image is downsampled hierarchically using a spatial-to-channel rearrangement approach to obtain multi-layered downsampled feature maps. A multi-branch convolutional structure is used to enhance the receptive field of each downsampled feature map, resulting in multi-scale visual features. In the text semantic enhancement process, at least one cue vector most relevant to the aerial image is selected from a cue vector library. The cue vector is semantically enhanced to obtain enhanced semantic features, which are then fused cross-modally with the multi-scale visual features. A detection head is then used to identify the target based on the cross-modal fused features. This invention improves the accuracy, robustness, and generalization ability of small target detection in complex environments.

This invention relates to the field of smart terminal technology and discloses a display device and a display control method. The display device includes a display and a controller configured to: when playing first media data with first media data parameters in a first projection window of a projection interface, in response to a second operation command for playing second media data in a second projection window, acquire second media data parameters of the second media data; if it is determined that the second media data does not meet the projection conditions, stop receiving the first media data and control the display to play the second media data in the second projection window; if it is determined that the second media data meets the projection conditions, control the display to continue playing the first media data in the first projection window and play the second media data in the second projection window. Applying this solution can improve the user's projection experience.

The application discloses a kind of based on digital human segmentation MRI image splicing and fusion method, comprising: the MRI data of different parts of human body obtained by nuclear magnetic resonance scanning is first registered after being preprocessed such as noise reduction, using the resolution, orientation etc. of reference image and floating image after registration, further realize the transformation of floating image between image coordinate system and world coordinate system, simultaneously based on trilinear interpolation interpolation and operation in the above spatial transformation process.The application realizes the seamless fusion of the three-dimensional image to be spliced in high and low frequency direction, effectively utilizes image high and low frequency component information.The application not only simplifies the two-stage image splicing and fusion process of traditional splicing method, i.e.fusing overlapping area first and then splicing non-overlapping area, and greatly improves the overall splicing and fusion accuracy of segmented MRI data.

The application discloses an unmanned ship underwater target intelligent identification method based on an imaging sonar, and relates to the fields of unmanned operation platforms and target identification. The application is aimed at the requirements of unmanned ship navigation and tasks, considers the task characteristics of the unmanned ship, and specifically adopts a forward-looking sonar to perform target ranging positioning and accurate identification, and based on machine learning and, realizes thorough water area perception, target detection and accurate identification for underwater targets. The application can improve the underwater target identification performance of the unmanned ship.

This invention discloses a method for detecting minute defects in cigarette boxes based on a CDM-YOLOv8 network, comprising: Step 1, acquiring an image of the cigarette box surface and constructing a defect detection dataset; Step 2, performing feature extraction enhancement on the input image, extracting defect-related features through multi-branch convolution, deformable convolution, and spatial attention mechanisms; Step 3, dynamically fusing features at different scales, and performing frequency domain banding processing on the fused features during the downsampling stage, employing a differentiated downsampling strategy to preserve defect edge and texture information; Step 4, outputting the category and location information of the defects based on the detection head. This invention solves the problems of easy loss of minute defects in cigarette boxes during downsampling and easy missed detection in complex backgrounds. By enhancing feature representation capabilities and preserving high-frequency defect information while ensuring computational efficiency, it improves the detection accuracy of minute defects in cigarette boxes and reduces the missed detection rate.

This invention relates to the field of UAV pose map optimization technology, and particularly to a method for optimizing the pose map of a UAV monocular camera. The method includes: blurring different image frame data, constructing a Gaussian pyramid, and downsampling; determining candidate feature points by subtracting Gaussian blurred images of adjacent scales; accurately determining the positions of candidate feature points on the image frame; removing low-contrast candidate feature points and edge response feature points to obtain the final feature points; and using the LM algorithm to adjust the UAV attitude parameters and optimize the pose map for discontinuous image frame data. The process of Gaussian difference point interest detection on continuously acquired image frame data suppresses noise in the image frames, effectively smoothing noise in the image. The resulting pose map is smoother with smaller gradient changes, improving the robustness of attitude estimation. The pose map optimization process expands the scope of pose map optimization, allowing optimization even for discontinuous images.

This application relates to an image processing method, apparatus, and computer device. The method includes: downsampling an image to be processed to obtain a downsampled image; generating an initial illumination image based on pixel information of each pixel in the downsampled image; performing FGS filtering on the initial illumination image to obtain an intermediate illumination image; performing brightness transformation and upsampling processing on the intermediate illumination image to obtain a target illumination image of the same size as the image to be processed; and using the target illumination image to enhance the brightness of the image to be processed to obtain the target image. This method can reduce the computational load in the image enhancement process without affecting the image enhancement effect, making it suitable for computer devices with lower computing performance and expanding its applicability.

The present application relates to a kind of flame and smoke detection method based on improved YOLO11, comprising: the image of target to be detected is collected, the image of target to be detected is input into improved YOLO11 model, and detection result is obtained;The improved YOLO11 model is obtained using training set training;The training set includes: original target image and flame and smoke label;The improved YOLO11 model includes: replace the conventional down-sampling layer in backbone network by detail-context collaborative down-sampling module, use dynamic double-feature fusion module to reconstruct feature interaction unit in feature fusion network, and use shared regression and asymmetric classification module to replace original unified classification detection head.The present application improves the performance of flame and smoke detection under complex environment.

The application belongs to the technical field of tactile sensing, and particularly relates to a pressure sensing system based on electroluminescence. The pressure sensing system comprises a light emitting module and a light sensing module. The light emitting module comprises a transparent electrode layer / transparent interdigital electrode layer, an electroluminescence layer, a porous dielectric layer and a stretchable electrode layer which are sequentially stacked from bottom to top. The light emitting module is used for sensing the pressure distribution applied to the surface and generating light with an intensity corresponding to the pressure size in the pressure area. The light sensing module is used for collecting the spatial position distribution and intensity information of the light. The application first proposes a new mechanism of electroluminescence tactile sensing based on the porous dielectric layer, realizes wide-range regulation of the light brightness from the non-light emitting state to the saturated light state, and establishes a direct physical mapping relationship between the applied pressure and the light brightness. The application fundamentally solves the pain point that high resolution, low cost and simple collection cannot be achieved simultaneously in tactile sensing, and provides a new technical path for flexible electronic skin.

The application relates to the technical field of chip circuits, in particular to a special chip ADC circuit for a retinal prosthesis, which comprises a sampling switch module, a capacitor array module, a dynamic comparator, a digital control logic module and a digital correction module; the capacitor array module comprises a P-end capacitor array and an N-end capacitor array, the P-end capacitor array comprises a plurality of first capacitors connected in parallel, and each first capacitor is connected with a first control switch; the N-end capacitor array comprises a plurality of second capacitors connected in parallel, and each second capacitor is connected with a second control switch; the same direction end of the dynamic comparator is connected with the end capacitor of the P-end capacitor array, and the reverse end of the dynamic comparator is connected with the end capacitor of the N-end capacitor array; the digital control logic module is connected with the output end of the dynamic comparator; and the digital correction module is connected with the output end of the digital control logic module. The ADC circuit provided by the application is used for converting a sensor analog signal into a digital signal and realizes low power consumption and high resolution.

This disclosure presents embodiments of a counter-drone reconnaissance method, apparatus, electronic device, and computer-readable medium. One specific implementation of the method includes: extracting object features from millimeter-wave radar data collected against a preset electronic fence airspace to generate an object feature information group; performing radio frequency (RF) signal reconnaissance to generate an object RF information group; identifying object RF information in the object RF information group that meets preset signal filtering conditions as candidate RF information, obtaining a candidate RF information group; performing infrared detection to obtain an infrared detection result group; removing interference from object feature information in the object feature information group that represents non-drone targets to generate a drone feature information group; performing counter-drone jamming based on the drone feature information group and performing counter-drone source tracing to generate a drone reconnaissance result group. This implementation can improve the accuracy of drone target detection.

This invention belongs to the field of satellite remote sensing and red tide detection technology, and discloses an integrated method and system for generating and identifying broadband 3D samples of dominant red tide species. The method constructs an integrated model for generating broadband 3D red tide samples and identifying dominant species based on deep learning. It utilizes a red tide image generation module based on spectral feature transfer to obtain expanded samples of different dominant red tide species. A red tide dominant species identification module is constructed by integrating multi-scale feature extraction and cross-spatial attention mechanisms. The module is trained using a student-teacher semi-supervised learning model. Experimental results show that the model has good adaptability and can effectively identify three dominant red tide species: *Noctiluca scintillans*, *Noctiluca chloroticus*, and *Hacochloa erythrophora*, with an overall identification accuracy of 94.48%, which is 3.52%–8.66% higher than other comparative methods, providing a basis for red tide prevention and management.

The invention belongs to the technical field of optical microscopic imaging, and particularly relates to a single objective lens light sheet microscopic imaging system, which comprises an exciting light modulation light path, a fluorescence detection light path and a microscopic imaging system, and is characterized in that the exciting light modulation light path is used for generating an illumination light sheet to excite fluorescence, and specifically comprises a laser, a beam expanding collimating lens group, a modulator, a scanning system and the like. The microscopic imaging system is used for transmitting an illumination light sheet and collecting light emitted by a sample, and comprises a dichroscope, a galvanometer module, an image rotating system, a tubular lens, an objective lens and the like. And the fluorescence detection light path comprises a relay lens group, a modulation element, a band-pass optical filter, a camera and the like. According to the invention, tasks of light sheet illumination and fluorescence collection in a traditional double-objective light sheet microscope are completed through a single objective, a remote focusing system or a micro-mirror reflection structure commonly used in an existing single-objective light sheet microscope does not need to be used, and a light sheet orthogonal to a focal plane is adopted for illumination. Compared with the existing light sheet microscope technology, the method has higher usability and flexibility, allows free switching of objective lenses under the condition of not changing other light paths, is compatible with any objective lens and various samples, does not need any software processing including deskewing in the principle of an obtained image, can directly display and use an original image, and is high in practicability. The system has higher resolution and is close to ideal isotropic imaging when various objective lenses are used for imaging.

This application provides a method for live streaming of satellite cloud images, relating to the field of satellite monitoring technology. The method includes the following steps: acquiring multiple cloud images observed by satellite; pre-setting grids of different sizes for the cloud images and classifying the cloud images to obtain cloud images of different resolutions; cropping the cloud images of corresponding resolutions according to the pre-set grids to obtain corresponding slices; grouping each slice according to time and creating video slices; and loading relevant information from the video slices onto the user terminal to display satellite cloud image animations according to the window size and position. This method can deliver high spatiotemporal resolution meteorological satellite cloud images to the user terminal in a timely manner, providing users with low-latency and high-timeliness cloud image services, thereby achieving live streaming of satellite cloud image animations, meeting weather monitoring needs, and providing technical support for meteorological forecasting services.

The present invention addresses the problem of providing a display device with which it is possible to brighten a decorative surface and to prevent a decrease in resolution or brightness of an aerial image. A solution is provided. A display device (100) is provided with a display (110), a first polarization beam splitter (120) that reflects light output from the display (110), a lambda / 4 wavelength plate (130), a retro-reflector (140), and a decorative sheet (150) that transmits light of an aerial image. And a second polarization beam splitter (160) that is disposed between the decorative sheet (150) and the first polarization beam splitter (120) and that aligns the transmission axis in the same direction as the direction in which the light (L2) of the aerial image is transmitted.

This application discloses an image processing method, apparatus, device, and storage medium, belonging to the field of artificial intelligence technology, and particularly relating to cloud computing, big data, or databases in the cloud technology field. The embodiments of this application can randomly select a processing method to degrade a high-resolution first sample image to obtain a low-resolution second sample image. This eliminates the need for manual processing, significantly reducing labor costs and improving the efficiency of acquiring low-resolution images. Furthermore, during training, a different processing method can be selected for degradation processing each time, ensuring that the trained target image processing model can perform good image processing on images processed by various methods, adapting to a wider range of image processing scenarios. Therefore, this target image processing model has good applicability.

The application discloses a pathological image color restoration method and a scanner based on deep learning, and the method comprises the following steps: reducing the resolution of input data and target data based on a bilateral grid downsampling technology; training a neural network model for the first time by using the input data and the target data after the resolution is reduced; improving the resolution of the input data and the target data after the resolution is reduced based on a bilateral grid upsampling technology; and training the neural network model for the second time by using the input data and the target data after the resolution is improved, so that the training speed of the neural network model is improved, and the staining effect of the pathological image collected by a digital pathology scanner is improved.

This application relates to the field of meteorological satellite technology and provides a meteorological satellite Earth operational service system, comprising: a data acquisition module for acquiring basic data; a data processing module for preprocessing the basic data; and a data product service module for publishing and providing data product services to users. The data processing module includes a data preprocessing unit, which further includes: a multi-resolution cloud image time-density encryption component for generating time-encrypted multi-resolution cloud image data; a high-resolution cloud image data reconstruction component for generating spatial high-resolution cloud image data; and a visible light cloud image generation component for generating visible light cloud image data using infrared cloud image data. This application implements functions such as encrypting low-resolution time-density cloud image data, reconstructing low-resolution cloud image data to high resolution, and automatically generating visible light cloud image data using infrared cloud image data.

The method for predicting river sand body by using geological pattern and seismic waveform dual constraints in dense well pattern relates to the field of reservoir geophysics, and solves the problem of uncertainty in interwell prediction caused by strong heterogeneity of reservoir and interference of thin layer in the process of seismic reservoir prediction. The method comprises the following steps: S1, analyzing and evaluating the quality of seismic data to determine the tuning thickness of the target layer; S2, establishing a geological-seismic knowledge base of river sand body; S3, classifying the geological response mode of reservoir based on the established geological-seismic knowledge base of river sand body; S4, establishing a geological-seismic response model of reservoir based on the classification of the geological response mode of reservoir; S5, selecting sensitive seismic attributes of different types of sand body; S6, analyzing and evaluating the prediction effect. The method improves the prediction accuracy of interwell river sand body.

This application discloses an image processing method, apparatus, device, and storage medium, belonging to the field of artificial intelligence technology, and particularly relating to cloud computing, big data, or databases in the cloud technology field. The embodiments of this application can randomly select a processing method to degrade a high-resolution first sample image to obtain a low-resolution second sample image. This eliminates the need for manual processing, significantly reducing labor costs and improving the efficiency of acquiring low-resolution images. Furthermore, during training, a different processing method can be selected for degradation processing each time, ensuring that the trained target image processing model can perform good image processing on images processed by various methods, adapting to a wider range of image processing scenarios. Therefore, this target image processing model has good applicability.