95results about "Counting objects with random distribution" patented technology

The invention belongs to the technical field of computer images, and provides an object counting method and device for enhancing text guidance by utilizing frequency characteristics. The method comprises the following steps: inputting a query image to a visual encoder to obtain visual features; inputting the object description text to a text encoder to obtain text embedding; fusing the visual features and the text features by using a fusion network to obtain fusion features; the fusion features are input into a decoder to obtain a density estimation graph of the object, the decoder comprises K cascaded adaptive frequency selection modules and one output layer, and the kth adaptive frequency selection module comprises a first convolution unit, an adaptive frequency selector and a first up-sampling unit; the kth self-adaptive frequency selector carries out filtering processing on the amplitude spectrum and the phase spectrum of the output characteristic of the first convolution unit in the frequency domain, and converts a filtering processing result into a spatial domain; according to the method, related frequency components are dynamically emphasized in decoding, the space domain and frequency domain features are combined, and accurate object positioning and accurate counting are achieved.

To provide a method of counting the number of round bars allowing for correctly counting the number of round bars irrespectively of the position of a rest surface.SOLUTION: A method of counting the number of round bars includes: acquiring height data in an upper-half outer periphery of a plurality of round bars arrayed at a constant interval in an array direction; taking a highest position of obtained height data as a reference position and identifying a position where height becomes minimal or minimum respectively on positive and negative sides in the array direction within a predetermined range determined from a diameter of the round bar with reference to the reference position as a boundary; adding a range from a negative minimal or minimum position over to a positive minimal or minimum position through the reference position, as an existence range of one round bar, to the number of round bars; taking a highest position of remaining height data excepting height data present in the existence range of the one round bar as a next reference position and identifying a position where the height becomes minimal or minimum on positive and negative sides respectively in the array direction within a predetermined range determined from the diameter of the round bar with reference to the next reference position as a boundary; and adding the same as a next existence range of a round bar to the number of round bars into calculation of the number of round bars.SELECTED DRAWING: Figure 3

The present invention belongs to the field of tea tree plucking, and specifically relates to a device for automatically identifying and counting tea tree buds, comprising a movable guide rail and an electric slider I, each movable guide rail being slidably connected to at least two electric sliders I. The present invention achieves this by inserting a lever and a baffle between tea trees, enabling the lever and the baffle to pry the leaves and buds on the upper portion of the tea tree. The lever then moves the leaves and buds on the upper portion of the tea tree, thereby preliminarily removing water droplets adhering to the leaves and buds on the upper portion of the tea tree. The baffle then moves again to pry the leaves and buds on the upper portion of the tea tree. The movement of the baffle is blocked by the leaves and buds on the upper portion of the tea tree, causing the baffle to bend. Simultaneously, the leaves and buds on the upper portion of the tea tree are also pushed by the baffle, causing them to bend. When the baffle gradually separates from the leaves and buds on the upper portion of the tea tree, the tea tree rebounds, thereby further removing water droplets adhering to the leaves and buds on the upper portion of the tea tree.

A hole counting device is provided with: an image acquisition unit that acquires one or more images obtained by capturing an image of a plurality of holes that capture a target substance; and a counting unit that counts the number of fluorescent holes among the plurality of holes for each of the one or more images acquired by the image acquisition unit, and that counts the number of fluorescent holes by excluding fluorescent holes among adjacent holes among the plurality of holes.

Properly manage the cleaning of ion exchange resins. [Solution] The ion exchange resin cleaning system 1 comprises a container 2 for cleaning the ion exchange resin 3, a cleaning water supply pipe L2 for supplying cleaning water to the container 2, a discharge pipe L4 for discharging the cleaning wastewater, and a measuring device 5 connected to the discharge pipe L4 for measuring the water quality of the cleaning wastewater. The measuring device 5 comprises an evaporation unit 52 that evaporates the cleaning wastewater to form residual particles, and a measuring unit 53 that measures the number of residual particles.

According to the method and the system for auditing the multimedia content of the PIS system in real time, the AI technology is deeply integrated into the existing PIS system architecture, so that the content of the PIS system is automatically audited and processed without delay. The invention provides a method for auditing multimedia content of a PIS system in real time. The method comprises the steps that 1, the PIS system generates the multimedia content; 2, judging whether the source of the multimedia content in the step 1 is a PIS system center side or not, if yes, entering a step 3, and if not, entering a step 4; step 3, judging whether the type of the multimedia content is a video stream or not, if so, entering step 5, and if not, entering step 6; and step 4, preprocessing the multimedia content to obtain a frame-cut picture, and auditing the obtained frame-cut picture in real time. And 5, auditing the video stream in real time. And step 6, auditing the text information in real time.

1. A method for operating a field crop transporting machine, in particular a field crop harvesting machine (2), comprising the steps of acquiring sensor data (3a, 3b), calculating mass data by an evaluation device (14) based on the sensor data, and providing yield data (16) calculated on the basis of at least the mass data, wherein the evaluation device (14) generates, based on at least the sensor data (3a, 3b), the mass data and / or the yield data (16), an adjustment signal (18) for adjusting at least one separating element of a separating device (20), the separating device (20) being configured to separate a first part of a harvested material (12) from another part of the harvested material (12).

To provide a recognition system of a chip having a setup capable of recognizing the color of a chip according to an image and counting the quantity of chips under a different illumination environment.SOLUTION: In a chip recognition system 10, a chip W is configured to at least partially have a specific color 121 showing the value of the chip W. The chip recognition system 10 includes: a recording device 11 for recording a state of the chip W as an image by using a camera 212; an image analysis device 14 for recognizing at least two colors of the specific color 121, and a reference color 4a differing from the specific color 121 existing in the recorded image by analyzing the image; and a recognition device 12 at least including an artificial intelligence device 12a for identifying the specific color 121 of the chip W by using an image analysis result by the image analysis device 14. Multiple images of the chip W irradiated with light having different illuminance, and the reference color 121 are taught to an artificial intelligence device 12a of the chip recognition device 12 as teacher data.SELECTED DRAWING: Figure 1

The method for estimating the accumulated mass of solid microparticles on a surface comprises describing the variation of the accumulated mass of the solid microparticles on said surface over time with a model defined according to a differential equation.

Method and apparatus (1) for detecting passengers getting on and / or getting off a means of transportation (T), comprising a) an acquisition phase (P1), wherein at least one image is acquired which comprises at least one portion depicting at least one portion of a door of said means of transportation (T), b) a processing phase (P2), wherein it is determined whether said door is in a closed state or in an open state on the basis of said at least one image, and a detection phase (P3), wherein at least one passenger getting on or getting off said means of transportation (T) is detected when said door is in the open state.

The concentration of non-volatile dissolved substances in the water flowing through the water treatment system must be properly managed. [Solution] The water treatment system 1 has a measuring device 5 that introduces the water flowing through the water treatment system 1 as the water to be measured and measures the water quality of the water to be measured. The measuring device 5 has an evaporation unit 52 that evaporates the water to be measured to form residual particles, and a measuring unit 53 that measures the number of residual particles.

The utility model discloses an anti-reflection insect sticking plate data collection and detection device, and mainly relates to the field of intelligent agriculture. Comprising a box body with an opening in the top, an insect sticking plate is placed at the bottom in the box body, a telescopic rod is arranged on the outer side of one end of the box body, a fastening bolt used for fixing the length of the telescopic rod is in threaded connection with the telescopic rod, a transverse rod is arranged at the top end of the telescopic rod, and a camera electrically connected with the Raspberry Pi is arranged at the end, away from the telescopic rod, of the transverse rod. The beneficial effects of the utility model reside in that the insect sticking plate is placed at the inner bottom of the box body, the box body prevents external sundries from adhering to the insect sticking plate in the shooting process, the accuracy of data analysis is ensured, light around the insect sticking plate can be shielded, the problems of light reflection, light pollution and the like in the shooting process are avoided, the quality and the effect of shot pictures are ensured, and the shooting efficiency is improved. And then the collected pictures are transmitted to the inside of the Raspberry Pi, and corresponding types and numbers are quickly and accurately counted by using a deployed corresponding target recognition algorithm, so that the method is more practical.

The application relates to a crowd behavior attribute counting method, system and product, and belongs to the field of computer vision.The counting method comprises the following steps: acquiring a complex crowd image; constructing a multi-scale feature fusion attention mechanism crowd behavior attribute counting neural network trunk; training the multi-scale feature fusion attention mechanism crowd behavior attribute counting neural network trunk based on the complex crowd image; acquiring a complex crowd image to be counted; and inputting the complex crowd image to be counted into the trained counting neural network to obtain a counting result.The above scheme in the application is suitable for dividing the behavior attributes of large-scale high-density crowds and detecting the number of crowds, and effectively improves the accuracy of detecting the number of specific crowds.

The high-precision predatory mite counting device comprises a base, a temperature box, a stereoscopic microscope, a counting structure, a walking column and a dismounting assembly, a positioning seat is driven to move through cooperation of a moving motor, a threaded rod, a threaded ring and a threaded block, so that the counting structure enters the temperature box and is stored in the temperature box with the environment temperature being 36 DEG C for 2 h, and then the predatory mites are counted. After all the predatory mites climb out and are limited by an insect sticking plate to move, the counting difficulty is reduced, a counting plate is moved out of the temperature box through a moving motor, a dismounting column drives a reset column to move, the reset column drives a reset plate to move, and the reset plate drives a limiting column to move and extrudes a reset spring; the relative positions of the limiting columns and the limiting holes are controlled, so that the positioning seat and the dismounting seat are quickly dismounted, the counting structure is conveniently moved to the position of the stereoscopic microscope, manual counting one by one is carried out under the stereoscopic microscope, and the working efficiency is improved.

The invention relates to a surgical instrument counting device for counting one or more different types of tools (h) for use in a surgical procedure, which comprises: an image-capturing camera (2); an electronic device (3) connected to the camera (2) and linked to a processing unit (3.1) that processes the images captured by the camera and executes counting algorithms; software with image recognition algorithms that uses artificial intelligence and computer vision, which is installed in the processing unit (3.1) and is capable of detecting and counting one or more different types of tools (h), including groups or families of tools, and capable of self-learning; and a support (4) suitable for mounting and positioning the camera (2) on a surface (5) on which tools (h) forming the set of instruments necessary for a surgical procedure are disposed.

Exemplary methods and systems for identifying suspect cytological specimens containing target cells are disclosed. One exemplary method includes acquiring a first image associated with a first region of the cytological specimen through a first objective lens, acquiring a second set of one or more images associated with a first subregion of the first region through a second objective lens, identifying a first number of target cells, and determining whether the first number of target cells is greater than a threshold number. If the first number of target cells is greater than the threshold number, the exemplary method prompts a warning. If not, the exemplary method further includes acquiring a third set of one or more images associated with a second subregion through a second objective lens, and identifying a second number of target cells associated with the second subregion.

The invention relates to a neutron spectrum and proton spectrum distinguishing measurement method and device based on a multi-ball measurement system, and the method comprises the steps: obtaining a current neutron and proton spectrum through employing an SAND-II few-channel spectrum unfolding algorithm based on a neutron and proton response function matrix of the multi-ball measurement system and an original count obtained through a to-be-measured field test; obtaining an original deviation between the measured value and the calculated value; reducing the count of each channel of the current neutron spectrum according to a set proportion, and calculating based on the SAND-II few-channel spectrum unfolding algorithm again to obtain a new proton spectrum, a new proton count, a new neutron spectrum and a new neutron count, and obtaining a new deviation between the total count and the original count; obtaining a plurality of deviations by changing the set proportion for multiple times; and finally, taking the neutron spectrum and the proton spectrum corresponding to the minimum value in all the deviations as measurement results. According to the invention, the neutron and proton real-time distinguishing measurement with relatively wide energy range and relatively high precision in a high-altitude region of the earth or in other neutron-proton mixed fields is realized.

To provide an information processing device that can more accurately grasp the storage status. [Solution] The information processing device according to the present invention comprises: a distance measurement information acquisition unit that acquires distance measurement information of a space including a three-dimensional virtual space area of ​​a predetermined size by a distance measuring sensor mounted on a moving body that moves based on a self-position estimation means; a calculation unit that calculates the amount of space occupied by an object present in the three-dimensional virtual space area based on the acquired distance measurement information of the three-dimensional virtual space area and pre-stored topographic information of the space including the three-dimensional virtual space area; and a request information generation unit that generates request information requesting the replenishment of the object based on the time-series change in the amount of space occupied by the object.

The invention discloses a tobacco insect image recognition and counting method based on YOLOv5 and a micro-service architecture, and the method comprises the following steps: S1, image acquisition, S2, image processing and data enhancement, S3, model training, S4, to-be-detected image input, S5, detection result writing into a text file, S6, statistics, and S7, packaging a statistical result in a system, and carrying out the data rendering of a front end. And S8, returning a statistical result. The method has the advantages that through fusion of deep learning algorithm optimization and distributed architecture design, efficient intelligent analysis service for tobacco insects is constructed. The system adopts a three-stage technical framework: firstly, performing weight training on a model level by using YOLOv5, reconstructing a backbone architecture through a lightweight feature extraction network, and enhancing a small target feature expression ability in combination with a cross-level attention mechanism; secondly, building a FastAPI-based micro-service, carrying out asynchronous processing on tasks, and realizing request distribution and dynamic scheduling of computing resources; and finally, realizing elastic expansion of algorithm service through a containerized deployment scheme.

To automate inspection work more simply and with higher accuracy.SOLUTION: An image inspection device according to one aspect of an embodiment comprises a control unit. The control unit acquires captured images of picked items. Furthermore, the control unit performs simplified training on a base model, which is a large-scale pre-trained AI model, using at least one of the captured images as a sample image. Further, the control unit executes an article inspection process for detecting and counting the article from the photographed image using the base model on which the simple instruction has been performed. In the inspection process, the control unit counts the articles after adjusting at least the size of the articles to the detection result by the base model.SELECTED DRAWING: Figure 2

The invention discloses an intelligent clinical material management system, and relates to the technical field of medical material management, and the system is characterized in that an Internet of Things sensing module is installed in a material storage area, environment parameters are updated in real time, and material counting authentication is carried out. When the materials flow, the sensing module identifies and authenticates the materials and then generates normal counting information. And the abnormal counting module processes data which are not passed or not authenticated, and abnormal counting information is generated. The first early warning module carries out inventory early warning identification in combination with the environment parameters and the counting information, and the second early warning module carries out further early warning based on an inventory demand prediction result. And the visual management module carries out overall early warning management according to the early warning result. The technical problems that due to the fact that an existing clinical material management system depends on manual counting, material counting is time-consuming and labor-consuming, errors are prone to occurring, and real-time and accurate tracking management of materials cannot be achieved are solved, and the technical effect of improving the efficiency and accuracy of inventory management is achieved.

The utility model relates to the technical field of counters, and provides a handheld tobacco leaf counter, which comprises a shell provided with a containing cavity, a scanning window and a display window, and the scanning window and the display window are communicated with the interior of the containing cavity; the circuit board is arranged in the accommodating cavity, and a processor is arranged on the circuit board; the display screen is arranged in the display window and is electrically connected with the circuit board; the scanning screen is arranged in the scanning window and is electrically connected with the circuit board; the camera is arranged in the accommodating cavity and is electrically connected with the circuit board; the power supply assembly is arranged in the accommodating cavity, is electrically connected with the circuit board and is used for supplying power to the circuit board; the multiple adjusting keys are arranged on the first side face of the shell, and the adjusting keys are connected to the circuit board; the handle is arranged on the second side surface of the shell; and the scanning key is arranged on the handle and is connected to the circuit board. According to the technical scheme, the problem that the counting workload is large due to manual counting of the tobacco leaves in the prior art is solved.

The application discloses a kind of crop kernel intelligent counting and internal quality multidimensional measurement system based on multistage drop difference dispersion and edge cloud cooperation, system includes multi-channel intelligent transfer warehouse machine electric feeding device, multistage ladder dynamics drop difference conveying device, inverted multispectral transmission imaging perception module, deep learning adaptive measurement module and automatic weighing recovery module.Parameter hot load is realized by scanning code and internet of things, adaptive anti-blocking feeding is realized by using rudder rotating baffle and two-stage vibration feeding disc coupling;Grain physical dispersion is realized by using multistage ladder gravity and collision tumbling;By inverted linear array CMOS camera and multi-band transmission light source, the characteristics of external contour and internal transmittance are synchronously acquired when grain falls.Lightweight YOLOv11 network is deployed on edge to accurately detect dense small targets, and gray threshold is combined to realize full and empty grain classification and statistics.The application can realize high-throughput, high-precision and automatic measurement of grain number, grain shape and quality parameters of multiple varieties of crops.

A spike number prediction device (10) includes: a spike number counting unit (14A) and the like configured to count, from image data obtained by imaging a two-dimensional unit region (frame F) provided in a wheat cultivation field (30), the number of wheat spikes from the frame F based on an image recognition technique; a correction unit (14B) configured to correct a spike number count value obtained by counting based on correlation information between a spike number count value obtained in advance by statistical processing and a spike number true value; and a spike number prediction unit (14C) configured to predict, based on a relative size relationship between a predetermined target range in the wheat cultivation field and the frame F, and a corrected spike number value after correction, the number of wheat spikes in the target range.

The counting accuracy of colonies is improved. A colony counting device causes an imaging section to image a test subject illuminated by sequentially switching an illumination direction of an illumination section to generate a plurality of pieces of image data with different illumination directions for the test subject, determines a reduced gloss pixel value based on pixel values ​​of pixels of a plurality of pieces of first image data corresponding to each of the pixels as a pixel value of each of the pixels of a test image when the reduced gloss test image is generated based on the first image data, and counts the colonies included in the test image.

The present invention discloses a medicine bottle counting method, system, device, and computer-readable storage medium. The method comprises: obtaining a preset target medicine bottle image; clustering the target medicine bottle image to obtain cluster center data; calculating, based on the cluster center data, intersection-over-union (IoU) data corresponding to the target medicine bottle image; comparing a preset threshold with the IoU data to obtain a comparison result; and counting the medicine bottles corresponding to the scattered points in the target medicine bottle image based on the comparison result. Embodiments of this method can achieve medicine bottle counting by clustering the target medicine bottle image, and improve the accuracy of the bottle counting.

The transducer group 10 forms a vertical detection plane in the water of the fish pen by arranging multiple ultrasonic transducers. A reciprocating control unit 101 causes the transducer group's vertical detection plane to rotate forward from a first position in the fish pen to a second position in the fish pen, and then rotate backward from the second position to the first position. A detection control unit 102 detects the number of fish in the fish pen as a detection count based on the transducer group's vertical detection plane for each of the forward rotation and the reverse rotation. A determination control unit 103 determines whether the fish in the fish pen are migratory fish based on the number of forward rotation detections during the forward rotation and the number of reverse rotation detections during the reverse rotation. A first estimation control unit 104 estimates the number of fish in the fish pen if the fish in the fish pen are not migratory fish. If the fish in the fish pen are migratory fish, the calculation control unit 105 calculates the swimming speed of the fish in the fish pen. The second estimation control unit 106 estimates the number of fish in the fish pen.

Detecting fetal maternal hemorrhage (FMH), measuring a total number of red cells in a maternal plus fetal blood samples, separating Rh+ cells from Rh- cells, and / or treating a fetal maternal hemorrhage through methods that involve labeling of red blood cells and assessment of the labeled cells in a gel card or a separation column operably connected to a detection apparatus that is configured to assess values of cells labeled in the various configurations described.

The present application relates to the field of particle detection, and specifically provides a method and device for identifying and counting ultrafine particles based on photoelectric effect, and a storage medium, comprising: obtaining photoelectric signals generated by a flow of particles to be detected passing through a photoelectric detection array; extracting original features of the photoelectric signals, combining time domain decomposition and frequency domain transformation to construct an initial signal feature matrix; performing multi-scale tensor decomposition and signal component screening on the initial signal feature matrix to generate enhanced photoelectric signals; determining a polarization coherence angle interval based on the enhanced photoelectric signals, extracting polarization energy features, analyzing polarization state conversion characteristics, and establishing a three-dimensional polarization feature fingerprint; performing adaptive segmentation processing on the enhanced photoelectric signals, extracting oscillation feature spectrum, and combining the three-dimensional polarization feature fingerprint to obtain a feature correlation matrix; and constructing a multi-dimensional classification criterion based on the feature correlation matrix, and determining a final particle count result accordingly. The present application improves the accuracy and recognition ability of ultrafine particle counting, and is particularly suitable for high-density micro-nano particle detection in complex environments.