153 results about "Image object" patented technology

Embodiments of the present description provide an image object detection method. The method comprises: on the basis of an image to be retrieved, an object description text, and an object retrieval condition, determining, by means of an object detection model, a target position of an object to be retrieved in said image, wherein the object description text is used for describing said object, and the object retrieval condition comprises at least one of a mask image, a pose, and a texture corresponding to said object.

A computer implemented method, system, and non-transitory computer-readable device that may be used in a remote deposit environment. Upon receiving a user request, based on interactions with the UI, the method implements an electronic deposit of a financial instrument by activating a camera on the client device to generate a live video stream of image data of a field of view of at least one camera, wherein the live video stream includes imagery of at least a portion of each side of the financial instrument. The method continues by extracting data fields based on the formation of image objects on one or more sides of the financial instrument from the live video stream of image data. An EFT conversion of extracted data fields may be processed during or subsequent to the extraction process. A message is sent from a payee to a payor requesting the EFT. Upon acceptance, an EFT to the payee occurs. Upon denial, the remote deposit process is completed.

The invention discloses a feature map enhancement method and related equipment thereof, and an image target detection method, and the method comprises the steps: obtaining a feature map, carrying out the local averaging and maximum pooling of an initial feature map, obtaining a local averaging feature map and a maximum pooling feature map, calculating the overall weight of a global pooling feature map through the global pooling operation and the one-dimensional convolution operation, and carrying out the one-dimensional convolution operation. And calculating a comprehensive weight of the local pooling feature map through a one-dimensional vector transformation operation and a one-dimensional convolution operation, further calculating an attention weight, and fusing the attention weight with the initial feature map to obtain an output feature map. Therefore, one-dimensional convolution is adopted to replace a multi-layer perceptron to perform feature channel interaction, feature extraction is performed on an interested target more accurately, the relationship between channels in a feature map can be concerned, local space information can also be concerned, important channels are selected and weighted processing is performed, so that efficient fusion of the channels and the space information is realized, and the accuracy of feature extraction is improved. Therefore, image detection can be completed more accurately.

The present invention relates to the field of remote sensing image object detection technology, particularly a remote sensing landslide object detection model, a method, a system and a readable medium. The remote sensing landslide object detection model provided by the present invention, firstly, the model pre-trains the embedding module, the location encoding module, and the attention feature extraction module on the first training set to realize the learning of the knowledge attributes associated with the auxiliary images; and then the attention feature extraction module and the Mask-RCNN model are further trained on the complete data set, so as to realize the fusion of the knowledge features and the visible image features, and comprehensively describe the characteristics of landslides, and the deep learning model is adopted to automatically extract the complex features to improve the detection capability of the landslide area.

The invention provides an automobile TARA analysis method and system based on multi-modal input and hybrid intelligence, and the method comprises the steps: extracting text entity information and image objects from vehicle design data, carrying out the intelligent matching of the text entity information and image objects, and constructing a structured asset list, detailed attribute description and a network topology structure diagram; performing threat identification and attack path deduction on the identified assets, and retrieving most relevant information fragments; and calling a large language model to generate an analysis result based on the multi-stage structured prompt, and outputting a standardized TARA report after post-processing. According to the invention, through the improved target identification model, the detection precision and robustness of tiny icons, slender buses and shielding elements in a complex and intensive automobile framework diagram are obviously improved; according to the method, the accuracy and authority of large language model reasoning are improved through path deduction and most relevant information fragments; the subjective deviation of manual analysis is eliminated while the analysis time is greatly shortened, and the high consistency of analysis results is ensured.

A monitoring system for mass packaging lines. In an aspect, a method includes creating image data by imaging objects on the mass packaging line using an imaging device while the objects are exposed to a light and using a processor having memory associated therewith to process the image data to determine a characteristic of at least one of the objects. The objects are conveyed on the mass packaging line in a configuration other than a single file.

This application relates to the field of medical technology and provides a medical application scenario matching method, electronic device, and computer program product. The medical application scenario matching method includes: acquiring a medical image sequence; determining image information of the medical images in the medical image sequence, the image information including key information, which includes one or more of the following: imaging object information, phase information, lesion detection information, and image quality information of the corresponding medical image; and outputting at least one target application scenario adapted to the medical image sequence based on the key information. Embodiments of this application can prevent doctors from using unsuitable medical image sequences in specific application scenarios, thus helping to improve doctors' work efficiency.

The invention relates to the technical field of X-ray imaging, and discloses an X-ray grating comprehensive imaging information extraction method and system. The method comprises the steps of obtaining and preprocessing original data; acquiring multi-dimensional interference parameters formed by grating phase drift distance, photon statistical noise density and imaging object deformation rate; dynamically calculating a phase correction coefficient, a noise suppression weight and information extraction confidence; phase compensation and noise filtering are executed based on the confidence coefficient, and structure and density information is extracted; parameter changes are monitored in real time, and the extraction process is updated; the system correspondingly realizes the method. The problem of low dynamic scene information precision caused by multi-interference coupling is solved, and the imaging information extraction stability and quality are improved.

The invention discloses a method for constructing knowledge graph nodes based on large model and image-text association, and relates to the field of knowledge graphs. The method comprises the following steps: analyzing a digital document to extract an image with bounding box coordinates and a text object; identifying a layout role of the text object, wherein a role system comprises a title type role and a text type role; for the image object, executing a layered decision logic to carry out image-text association, preferentially selecting a text of which the layout role is a title role as a description source by the logic, and if the logic fails, selecting a text class role text with the highest semantic similarity; quantizing an association confidence score representing the association reliability; and generating a knowledge graph image node containing the optimal text description and the associated confidence score. According to the method, hierarchical decision making is carried out by utilizing the layout structure information of the document, and quantitative confidence is given to each association result, so that the accuracy, the credibility and the interpretability of knowledge graph construction are improved.

A computer implemented method, system, and non-transitory computer-readable device that may be used in a remote deposit environment. Upon receiving a user request, based on interactions with the UI, the method implements an electronic deposit of a financial instrument by activating a camera on the client device to generate a live video stream of image data of a field of view of at least one camera, wherein the live video stream includes imagery of at least a portion of each side of the financial instrument. The method continues by extracting data fields based on the formation of image objects from one or both sides of the financial instrument from the live video stream of image data. The extracted data fields are converted, based on a payor agreement, into a recurring electronic funds transfer (EFT) schedule for future payments similar to the check.

The invention relates to the technical field of artificial intelligence and multi-modal large language models, financial science and technology and medical health, and particularly discloses a multi-modal reasoning task processing method and device based on selection of a visual token, a storage medium and computer equipment, and the method comprises the steps: receiving a to-be-processed image object and a text instruction; encoding the text instruction into a text token sequence, encoding a to-be-processed image object into a plurality of visual tokens, and determining a visual token set according to the visual tokens; an empty visual token subset is initialized, one visual token is iteratively selected from the visual token set every time and added into the visual token subset until a preset condition is met, and during selection every time, determination is carried out based on the semantic coverage increment of the remaining visual tokens; and splicing the selected visual token in the visual token subset with the text token sequence, and executing a multi-modal reasoning task based on a splicing result.

A computer implemented method, system, and non-transitory computer-readable device that may be used in a remote deposit environment. Upon receiving a user request, based on interactions with the UI, the method implements an electronic deposit of a financial instrument by activating a camera on the client device to generate a LIDAR managed live video stream of image data of a field of view of at least one camera, wherein the live video stream includes high quality confidence scored imagery of at least a portion of each side of the financial instrument. The method continues by extracting data fields based on the formation of image objects of each side of the financial instrument from the live video stream of image data. The extracted data fields are communicated to a remote deposit server to complete the remote deposit.

A video device (100) is provided with: a plurality of transmitters (101) for transmitting fluctuations to a measurement region; a plurality of receivers (102) that receive fluctuating scattered waves from the measurement region; and an information processing circuit (103) that uses the measurement data of the scattered waves to image an object in the measurement region, and that derives a scattered field function using the measurement data and the velocity vector of the object. Deriving a video function that is determined using the amount that is output from the scattered field function by inputting the position of the object to be video into the scattered field function, and video the object in the measurement region using the video function; the information processing circuit (103) changes the number of scattered waves reflected by the scattered field function due to the Doppler effect corresponding to the velocity vector.

Embodiments of the present disclosure disclose an instruction information storage method, device and medium based on an artificial intelligence speech model. A specific implementation of the method includes: obtaining a set of object noise reduction intensity information; in response to receiving image redrawing instruction generation information, obtaining image description information and a set of image object information; generating a corresponding mask image to obtain a set of mask images; for each image object information, performing a first generation step: in response to including the image object information, obtaining target object noise reduction intensity information, and determining a corresponding target mask image; packaging the target object noise reduction intensity information, the image description information, the target mask image and a target image to obtain packaging information; using a large language model, generating a corresponding image redrawing instruction information for each image; and storing the set of image redrawing instruction information. The implementation can efficiently and high-quality generate image redrawing instructions for target images to meet the diversified image needs of target objects.

A computer implemented method, system, and non-transitory computer-readable device that may be used in a remote deposit environment. Upon receiving a user request, based on interactions with the UI, the method implements an electronic deposit of a financial instrument by activating a camera on the client device to generate a live video stream of image data of a field of view of at least one camera, wherein the live video stream includes imagery of at least a portion of each side of the financial instrument. The method continues by extracting data fields based on the formation of image objects on one or more sides of the financial instrument from the live video stream of image data. An EFT conversion of extracted data fields may be processed during or subsequent to the extraction process. A message is sent from a payee to a payor requesting the EFT. Upon acceptance, an EFT to the payee occurs. Upon denial, the remote deposit process is completed.

A method for manufacturing a synthetic image device includes providing (S10) an array of focusing elements. An image layer is arranged (S20) near the focal length of the focusing elements, whereby a synthetic image composed of a magnified portion of the image layer becomes perceptible to a viewer. The image layer includes an array of image units, each image unit associated with a corresponding focusing element. The step of arranging (S20) the image layer includes creating (S22) a corresponding image object within each corresponding image unit in the image units. These image objects make an animation perceptible, the animation comprising a series of synthetic images that are continuously perceptible as the viewing direction changes. These image objects make each of the synthetic images in the series perceptible at a corresponding perceptible depth, the corresponding perceptible depth varying between the synthetic images in the series.

A method of artificial-intelligence-based robotic pipetting for spermatozoa preparation includes positioning a vessel containing a semen sample within a staging mechanism. The method includes using a robotic pipettor to make at least two droplets within a dish on the staging mechanism. The method includes using the robotic pipettor to connect the at least two droplets with a medium channel according to a programmable design commanded by an artificial intelligence / machine learning system (AI / ML system). The method includes using the robotic pipettor to deposit a quantity of sperm from the semen sample into one of the droplets. The method includes using the AI / ML system to optically scan the quantity of sperm to produce first and second image objects using an imaging system that includes a microscopy system, a camera system, and a lighting system. Creation of the image objects is separated by a specified time duration.

The embodiment of the invention provides an object loading method and device, and the method comprises the steps: obtaining object attribute information of a target object and object interaction information of the image object in response to a received loading request of the image object issued for the target object; according to the object attribute information of the target object and the object interaction information of the image object, request popularity information of the image object is determined, and different request popularity information corresponds to different page view ranges; and according to the request popularity information of the image object, determining at least one data cache node matched with the request popularity information, and processing a loading request of the image object through the at least one data cache node. According to the method, the data loading speed can be increased.

This invention discloses a user-generated content sharing system with fine-grained access control, specifically relating to the field of user-generated content sharing and data access control. It includes an end-to-end sharing module for writing published user-generated content into fragment identifiers based on text segments, image objects, and attachment objects, attaching the initial receiving scope and initial re-sharing action to the fragment identifiers, and generating an original shared copy. This invention solves the problem in existing technologies where, when receiving user-generated content, it is impossible to limit the content segments that can be brought out, the receiving object scope, and the re-sharing action based on the current shared copy by splitting user-generated content into fragments and generating an original shared copy.

An information processing device (100) comprises: an acquiring unit (121) that acquires image information representing a two-dimensional image; a determining unit (122) that determines a reference object to serve as a reference from among one or more image objects included in the two-dimensional image represented by the acquired image information, and, on the basis of the dimensions of the determined reference object, determines display information representing a display region in which the two-dimensional image is displayed in a virtual space; and an output unit (123) that outputs the determined display information.

A computing system for detecting objects in an image can perform operations including generating an image pyramid that includes a first level corresponding with the image at a first resolution and a second level corresponding with the image at a second resolution. The operations can include tiling the first level and the second level by dividing the first level into a first plurality of tiles and the second level into a second plurality of tiles; inputting the first plurality of tiles and the second plurality of tiles into a machine-learned object detection model; receiving, as an output of the machine-learned object detection model, object detection data that includes bounding boxes respectively defined with respect to individual ones of the first plurality of tiles and the second plurality of tiles; and generating image object detection output by mapping the object detection data onto an image space of the image.

An image object labeling method and circuit system for implementing the method, in which an image is first obtained, the image is divided into one or more blocks by object classification, each block is classified into a category and is assigned a category label, and depth information of each pixel in the image is estimated by a depth estimation method. Then, according to the category of each block, it is determined whether the depth information of each pixel in the block matches the category of the block to which the pixel belongs. When the depth information of any pixel in each block matches the category of the block to which the pixel belongs, weights are set according to the category labels of each block, and a post-processing procedure is performed on the image according to the weights of each block. Otherwise, if the depth information of any pixel does not match the category of the block to which the pixel belongs, it is considered as noise and the post-processing procedure is not used.

This invention discloses a remote sensing classification method and device for periglacial landforms. The method includes: establishing remote sensing classification rules for periglacial landforms, dividing periglacial landforms into primary and secondary periglacial landform types; collecting remote sensing images and digital elevation model data of the target area in permafrost regions at various resolutions, and performing radiometric calibration and atmospheric correction on the remote sensing images; performing first-scale segmentation and second-scale segmentation on the processed data to generate two-level image object layers, with the first-scale segmentation generating a primary image object layer corresponding to the primary periglacial landform type and the second-scale segmentation generating a secondary image object layer corresponding to the secondary periglacial landform type; extracting and analyzing features for each image object in the primary and secondary image object layers; and, based on the remote sensing classification rules for periglacial landforms, classifying the image objects in the primary and secondary image object layers into the corresponding primary and secondary periglacial landform types, respectively, and outputting a remote sensing classification map of periglacial landforms.

Provided are a method for generating a bounding box of an image target, an electronic device, a non-transitory computer-readable storage medium, and a computer program product. The method includes: obtaining a feature map based on one or more of a self-attention feature, a cross-attention feature, and a latent vector obtained in a process of generating an image including an image target or in a process of adding noise to the image and regenerating the image; and obtaining a bounding box of the image target based on the feature map.

1. Name of the product in this design: Graphical User Interface for Medical Imaging MPR Browsing in Electronic Devices. 2. Purpose of this design: This design is used for running programs and displaying information. 3. The key design features of this product are the graphical user interface displayed on the screen of the electronic device. 4. The picture or photo that best illustrates the key design points: Design 1 front view. 5. Other views have no design points, so rear view, left view, right view, top view, bottom view, and perspective view are omitted. 6. Design 1 is designated as the basic design. 7. Uses of the graphical user interface: for browsing MPR (multiplanar reconstruction) images of medical images, including two-dimensional images of the Axial, Coronal, and Sagittal planes, as well as three-dimensional images rendered in volume. 8. Human-computer interaction method of graphical user interface: Interact with the graphical user interface by clicking with the mouse to load the subsequent graphical user interface. 9. Description of the changing states of the graphical user interface: Design 1: Double-clicking the Axial image window in the main view of Design 1 displays the interface state change diagram 1; similarly, double-clicking the Coronal and Sagittal image windows will also display the corresponding interface state change diagrams; Design 2: Clicking the word "Coronal" in the Coronal image window in the main view of Design 2 will bring up a drop-down box, displaying the interface state change diagram 1; similarly, clicking the words "Axial" or "Sagittal" in the Axial or Sagittal image windows in the main view will also bring up a drop-down box; Design 3: Unchecking the corner mark in the main view of Design 3 will display the interface state change diagram 1; Design 4: Checking the zoom ruler in the main view of Design 4 will display the interface state change diagram 1; Design 5: Clicking the modify window width / window level tool (pen icon) in the main view of Design 5 will display the interface state change diagram 1. 10. Other situations requiring explanation: The specific image content and marking results in the interface vary depending on the image object and are not protected by this design.

The invention belongs to the technical field of optical imaging, and discloses a non-intrusive imaging method and device penetrating through a dynamic scattering medium, and the method comprises the steps: controlling a preset coherent object light beam to irradiate an object to be imaged, and forming an object light field; collecting a speckle intensity image of a speckle field formed by an object light field penetrating through the preset dynamic scattering medium in a far-field region, wherein the far-field region is a region of the preset dynamic scattering medium penetrated by the object light field; based on a four-moment correlation function of the speckle intensity image, analyzing to obtain a far-field mutual dry function; according to a function relationship between the far-field mutual coherence function and the object light field autocorrelation function, analyzing to obtain an autocorrelation function of the object to be imaged; and based on a phase recovery algorithm, reconstructing an image of the to-be-imaged object through the autocorrelation function. According to the invention, view field limitation caused by dependence on an optical memory effect is avoided, imaging can be completed through single exposure, a data acquisition process is simplified, and adaptability to a dynamic scattering medium and imaging efficiency are improved.

A method for manufacturing a synthetic image device includes providing of a focusing element array. An image layer is arranged in a vicinity of a focal distance of focusing elements, whereby a synthetic image composed of enlarged portions of the image layer becomes perceivable for a viewer. The image layer includes an array of image cells, each associated with a respective focusing element. The step of arranging the image layer includes creation of a respective image object within each respective one of said image cells. The image objects are such that an animation becomes perceivable, comprising a series of synthetic images perceivable in-series as the viewing direction changes. The image objects are such that each one of the synthetic images of the series is perceivable at a respective perceivable depth, changing between the synthetic images of the series of synthetic images.

Embodiments of the present application provide a method and device for generating a dynamic image based on audio, an apparatus, and a storage medium, relating to the field of natural human-computer interaction. The method comprises: first obtaining a reference image and a reference audio input by a user; then, based on the reference image and a trained generation network model, determining a target head action feature and a target expression coefficient feature, and adjusting the trained generation network model based on the target head action feature and the target expression coefficient feature to obtain a target generation network model; finally, based on the reference audio, the reference image, and the target generation network model, processing a to-be-processed image to obtain a target dynamic image; wherein the to-be-processed image is the same as an image object in the reference image; in this way, a corresponding digital person can be obtained based on a single picture of a target person; in this way, video acquisition work and data cleaning work are not required, the production cost of the digital person can be reduced, and the production cycle of the digital person is shortened.

The application relates to the field of medical image archiving, and discloses a sequential medium medical image archiving method, system, terminal and storage medium based on visibility root and reachability recovery control, which comprises the following steps: aggregating medical image objects into immutable archive segments and sequentially writing the medical image objects into a target area; after the writing is completed, a release record containing a segment identifier, an area identifier and a predecessor identifier is added to a release log; an atomic update of a visibility root pointing to the release record is independently controlled on a storage layer, the visibility root is a unique entry of a logical readable state; and all reachable release records are determined along an ancestor chain formed by the predecessor identifier, starting from the visibility root, and the corresponding immutable archive segments are external readable archive segments, so that archiving is completed. The physical writing completion is decoupled from the logical visibility release, the read visibility range is restricted through the visibility root, and the write area recovery condition is controlled, so that consistent readability, recoverability and controllable recovery of medical image archiving on a sequential medium are realized.

The invention provides a computer-implemented method, system and computer program product. The method comprises the following steps: receiving a plurality of training samples in an image object detection data set; constructing a corresponding scene tree for each training sample, wherein leaf nodes of each scene tree are object frames contained in the corresponding training sample; selecting a reserved object box set for all object boxes; for all the object frames, calculating the similarity between any two object frames; displaying the plurality of training samples, the object frames contained in the plurality of training samples and the information of the object frames in a two-dimensional plane; in response to the fact that the information of any object box is modified, the modification operation of the modified object box is spread in all the object boxes; the reserved object box set is selected again; and determining that the object frames in the object frame set reserved at the moment can be used for retraining the model in response to determining that the object frames with the information modified do not exist any more.