55 results about "Image query" patented technology

The invention provides a cross-modal retrieval method for semantic and vector fusion in a data space, which belongs to the field of cross-modal information retrieval, and comprises the following steps: firstly, collecting and preprocessing multi-modal data; generating modal embedding and storing by utilizing the pre-training model; a shared semantic space is constructed, cross-modal vector alignment is optimized through comparative learning, and a modal mapping network is designed to enhance the embedding projection effect; storing the aligned embedding by using a Milvus database, and constructing an HNSW index; user text or image query is processed, text query analyzes limiting conditions to generate enhanced embedding, and image query extracts characters through OCR and fuses the characters with image features to generate embedding; in a database, through condition screening and semantic similarity calculation, a Top-K candidate item is retrieved; performing multi-modal correlation sorting on the candidate results and returning the results; according to the method, the shared semantic space is constructed, the alignment effect of different modal embedding is optimized, efficient storage and index management of multi-modal embedding are carried out, and real-time retrieval of large-scale cross-modal data is achieved.

The present disclosure describes methods, systems, apparatus, and media for object identification and classification, utilizing multi-feature and multi-modal data. This includes shape, material, brand, price, odor, taste, tactility, and sound. The system integrates a server space for data processing, a querying device for iterative searches, and a data interface module for refining results. It features AI-driven image optimization, feature extraction, and pattern recognition, employing novel techniques for fusing multi-feature and multi-modal embeddings utilizing multi-head attention. Additionally, a linker module powered by two active learning with feedback loops AI models consolidates scattered data into a unified object information database. The system also employs novel AI algorithms for isolating the object of interest through a saliency map and semantic analysis, as well as for enhancing raw images with a GAN-autoencoder.

The present disclosure describes methods, systems, apparatus, and media for object identification and classification, utilizing multi-feature and multi-modal data. This includes shape, material, brand, price, odor, taste, tactility, and sound. The system integrates a server space for data processing, a querying device for iterative searches, and a data interface module for refining results. It features AI-driven image optimization, feature extraction, and pattern recognition, employing novel techniques for fusing multi-feature and multi-modal embeddings utilizing multi-head attention. Additionally, a linker module powered by two active learning with feedback loops AI models consolidates scattered data into a unified object information database. The system also employs novel AI algorithms for isolating the object of interest through a saliency map and semantic analysis, as well as for enhancing raw images with a GAN-autoencoder.

This disclosure describes a lightweight image query system that utilizes multiple lightweight models to quickly and efficiently generate responses to multimodal input queries. For example, in response to a multimodal input query, the lightweight image query system utilizes multiple lightweight context models to first obtain different types of context information based on the different input modes. The lightweight image query system then utilizes a lightweight large generative model (LGM) to quickly generate a query response using the different types of context information. By using lightweight models, including multiple lightweight context models and a lightweight LGM, the lightweight image query system can efficiently provide query responses to multimodal input queries in about half the time it takes conventional systems to return a query response.

The embodiment of the invention provides a nursing service monitoring method and device, equipment, a storage medium and a program product, and is applied to computer equipment, and the method comprises the steps: obtaining monitoring data of nursing service, employing a cue word engineering technology, carrying out the frame extraction processing of a video through a video analysis assembly, obtaining a plurality of groups of pictures, querying the video analysis rule configuration, and obtaining a monitoring result. Acquiring questioning points of the pictures, configuring and assembling cue words according to a video cue word rule, inputting the cue words into a large model to ask a question to the large model to obtain an analysis result of multiple groups of pictures, correcting, integrating, analyzing and judging according to a data processing rule to obtain a video analysis result, analyzing the audio through a voice recognition model to obtain an audio conversion text, and displaying the audio conversion text. And querying audio prompt word rule configuration to obtain a prompt word corresponding to an audio conversion text question point, inputting the prompt word into the large model to obtain an audio analysis result, and generating a nursing service monitoring report according to the video analysis result and the audio analysis result, thereby improving the monitoring efficiency of monitoring the nursing service quality.

The invention discloses a grain production-oriented cross-modal representation learning and retrieval method and system, and relates to the field of agricultural informationization, and the method comprises the steps: carrying out the multi-granularity semantic alignment of an image text pair in a grain production process based on an image-text bidirectional guidance fusion network, and obtaining a semantic segmentation image; performing image space decoupling and time sequence enhancement on a video text pair in a grain production process based on global semantic guidance to obtain a structured semantic image feature; constructing a text feature library and an image feature library; and determining a transmission plan matrix according to the modality of the to-be-retrieved data, generating query features of the to-be-retrieved data based on the transmission plan matrix, and outputting a text query result or an image query result by adopting a similarity measurement method according to the query features of the to-be-retrieved data, the text feature library and the image feature library. According to the method, deep fusion of cross-modal features can be realized, the semantic matching accuracy of the image and the text is improved, and rapid and accurate matching and retrieval between the image and the text are realized.

Systems, methods, and non-transitory computer-readable media implements related image search and image modification processes using various search engines and a consolidated graphical user interface. For instance, one or more embodiments involve receiving an input digital image and search input and further modify the input digital image using the image search results retrieved in response to the search input. In some cases, the search input includes a multi-modal search input having multiple queries (e.g., an image query and a text query), and one or more embodiments involve retrieving the image search results utilizing a weighted combination of the queries. Some implementations involve generating an input embedding for the search input (e.g., the multi-modal search input) and retrieving the image search results using the input embedding.

The invention belongs to the field of intelligent rail transit and computer vision, and provides a three-dimensional target detection and rail line identification method based on multi-modal fusion. According to the method, camera images, laser radar point cloud voxel features and point cloud features are extracted through deep learning, image query and point cloud query are generated according to an image query generator and a point cloud query generator, a unified query input detection head is formed through clustering fusion, and a target detection result is output. Meanwhile, a unified query generator is designed to generate a track line sensing query, and after fusion, a track line detection head is input to output a track line detection result. According to the method, multi-mode complementary information is effectively utilized, a coordinate system is unified to avoid conversion errors, and target detection and track line identification in a long-distance range in front of the track locomotive are realized by adopting a sparse query method.

This invention discloses a method and system for real-time monitoring and prediction of carbon intensity, belonging to the field of carbon emission monitoring technology. The method acquires and processes electricity-related data such as installed capacity and real-time load of each province hourly through an ETL data channel; it draws a map of China based on ECharts, dividing it into five color-level intervals according to carbon intensity values: 0-300, 301-500, 501-700, 701-900, and 901-1200 gCO2 / kWh; responding to user clicks on provinces, it displays detailed data for each province through indicator cards, circular progress charts, and one-sided bar charts; it calls a pre-trained STFCI hybrid model to predict carbon intensity hourly for the next 24 hours. This model integrates a 2-layer 128-neuron LSTM unit with an XGBoost unit with 100 trees and a learning rate of 0.1, outputting predicted values ​​after feature concatenation and a fully connected layer; the prediction results are displayed as a bar chart, marking customizable low-carbon threshold lines, highlighting low-carbon periods, and generating electricity consumption suggestions. The corresponding system includes a data interface, database, visualization, prediction, and WeChat service modules. The database adopts an InfluxDB+MySQL combined architecture, and the WeChat service module supports mobile text and image queries. The STFCI model of this invention has an average absolute error of only 12.3 gCO2 / kWh, significantly improving prediction accuracy, realizing hourly real-time monitoring and multi-dimensional visualization of carbon intensity, and providing precise decision support for power dispatching and energy conservation and emission reduction when combined with mobile services.

This application discloses a cross-modal representation learning and retrieval method and system for grain production, relating to the field of agricultural informatization. The method includes: performing multi-granularity semantic alignment on image-text pairs in the grain production process based on a bidirectional guided image-text fusion network to obtain semantically segmented images; performing image spatial decoupling and temporal enhancement on video-text pairs in the grain production process based on global semantic guidance to obtain structured semantic image features; constructing a text feature library and an image feature library; determining a transmission plan matrix based on the modality of the data to be retrieved; generating query features for the data to be retrieved based on the transmission plan matrix; and outputting text query results or image query results using a similarity measurement method based on the query features, text feature library, and image feature library. This application enables deep fusion of cross-modal features, improves the accuracy of image-text semantic matching, and achieves fast and accurate matching and retrieval between images and text.

The embodiment of the invention provides an image query method and device, equipment and a storage medium. The method comprises the following steps: determining a first group of images matched with a text query item from a first image set; determining a fused image feature by fusing a group of image features corresponding to the first group of images; and based on the fused image features, determining a second group of images from the second image set as a query result for the text query item. According to the embodiment of the invention, image query is carried out based on richer and more accurate fusion image features of the feature information, and the accuracy of image query can be effectively improved.

The present application provides an image query method, apparatus, and device, the method comprising: acquiring an initial image, the initial image comprising a first region of interest and a first noise region; generating a candidate image based on the initial image, the candidate image comprising a second region of interest and a second noise region; the image features of the second region of interest matching the image features of the first region of interest, and the image features of the second noise region not matching the image features of the first noise region; based on the initial image and the candidate image, querying a target image corresponding to the initial image from an image database; the image database being used to record images with identity information. Through the technical solution of the present application, an accurate target image can be queried based on the features of multiple frames of images to query a target image that matches the initial image. Even if only one frame of the initial image is provided, the target image can be queried based on multiple frames of images, thereby improving the performance of image queries.

An electronic device is provided. The electronic device includes a camera, a communication circuit, memory storing one or more computer programs, and one or more processors communicatively coupled to the camera, the communication circuit, and the memory, wherein the one or more computer programs include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the electronic device to extract, from an image obtained from the camera, a portion of the image including objects, determine a primary object to be searched for from among the objects in the image, determine an object associated with the primary object as a secondary object, from among other objects in the image, generate an image query including a portion of the image including at least one of the primary object or the secondary object, and including a request for information related to the primary object, and transmit the image query to a server through the communication circuit.

The application discloses a specific picture recognition method based on multi-modal, relates to the field of specific picture recognition, and comprises two parts of feature information extraction of pictures and texts and a specific picture matching strategy of FH-LANet, adopts an image matching idea to extract features of pictures through a multi-modal feature extraction network FH-LANet model, selects a specific picture as a query library picture, the query feature is not a single modal picture feature, but a text feature, similarity calculation is carried out by using the features of the input picture and the query feature, threshold judgment is then carried out, the matched picture and filtered text are matched again, noise data is filtered out, the picture that does not match the query picture is secondarily matched with the query text, and finally, the recognition result of the picture is obtained, and the specific picture in the mass pictures can be accurately found out.

The utility model discloses a wearable nursing worker housekeeping law enforcement instrument. The instrument comprises a camera shooting mechanism; the camera assembly is rotatably or fixedly arranged on the front surface of the camera mechanism; the control module is arranged in the camera mechanism and associated with the camera assembly, and at least one charging connector is arranged on the back face of the control module; the power supply mechanism and the camera shooting mechanism are attached to the inner side and the outer side of the clothes of the nursing and housekeeping personnel respectively and are magnetically attracted and positioned; the power supply assemblies are arranged in the power supply mechanism, power supply connectors are arranged on the front faces of the power supply assemblies, and the power supply connectors and the charging connectors conduct charging in a one-to-one or many-to-one mode in sequence. The nursing worker housekeeping law enforcement equipment can solve the problems that existing nursing worker housekeeping law enforcement equipment is low in pertinence and intuition of recorded content, short in endurance time and incapable of meeting the requirements of high endurance of the law enforcement equipment corresponding to nursing worker housekeeping long-time work, follow-up work image query and reward and punishment dispute handling convenience.

The embodiment of the invention relates to a medical image query and comparison system. The system comprises an image database, a query server and a plurality of first clients, and the query server is respectively connected with the image database and each first client. The image database is used for storing a plurality of image data records. The query server is used for performing multi-dimensional query on the image database based on the multi-dimensional query configuration sent by the first client; the first client is used for generating multi-dimensional query configuration, sending the multi-dimensional query configuration to the query server, displaying a query list according to server feedback data, generating a multi-selection target set according to a selection result of a user on the query list, and registering and aligning all images of the multi-selection target set; and the synchronous operation module is used for carrying out synchronous operation on loading images in other image areas according to operation actions of a user in any image area. On the basis of the method, the query operation can be simplified, the query efficiency is improved, the big data value is improved, and the operation convenience of multi-image comparison is improved.

The invention is suitable for the technical field of computer application, and provides a vehicle part chart query method and device, electronic equipment and a storage medium, the method comprises the following steps: in response to a chart query instruction triggered by a user, determining first named entity information corresponding to the chart query instruction; performing vector coding processing on the first named entity information to generate a chart query vector corresponding to the first named entity information; according to the chart query vector and a preset chart vector library, determining a target component chart corresponding to the chart query instruction; and sending the target part chart to the user. Therefore, the named entity information in the user chart query instruction is extracted, the image query vector is generated according to the named entity information, and the component chart corresponding to the chart query instruction is queried through the image query vector, so that the component chart query efficiency and accuracy are improved, and the automobile maintenance efficiency and accuracy are improved.

The embodiment of the invention discloses a city management case image recognition method and system based on a multi-modal large model. According to the embodiment of the invention, an image-text pair is constructed by collecting city management images and text data, description is generated for the images by using the multi-modal large model, and a text embedding model is finely adjusted to improve the image-text semantic alignment capability. According to the embodiment of the invention, text or image query can be accepted, the advantages of sparse retrieval and dense retrieval are combined through a mixed retrieval strategy, related information is accurately retrieved, and finally, deep reasoning is carried out by utilizing a multi-modal large model. The problems that image-text semantics are not fully aligned and the retrieval precision is insufficient are effectively solved, and the accuracy and reliability of complex image recognition in a city management scene are remarkably improved.

The invention provides a picture processing method and device, equipment, a medium and a product, and relates to the technical field of data processing, and the specific technical scheme is as follows: in a system switching process of a target server and a historical server, the historical server transmits first structured information of a historical picture to the target server, and the target server transmits the first structured information of the historical picture to the target server in each piece of index information; and taking the index information matched with the picture query condition as target index information, and sending the target index information to the terminal. And the terminal queries the target query picture in a historical server or a target server based on the target index information. According to the method, the historical picture does not need to be transmitted, only the first structured information needs to be transmitted, the data size of the first structured information is smaller than that of the historical picture, the data transmission time in the system switching process is saved, the data transmission efficiency in the system switching process is improved, and then the system switching efficiency is improved; and the target server can execute the picture query service as soon as possible.

The utility model discloses image inquiry equipment which comprises a base, a lifting device, a connecting arm and an imaging device. The lifting device is arranged on one side of the base in the first direction and can move in the first direction. The connecting arm is rotatably arranged at the end, away from the base, of the lifting device. The imaging device can rotate around the joint of the connecting arm and the imaging device in the first direction, the imaging device comprises a shell, a display screen and an imaging lens, the display screen and the imaging lens are both arranged on the shell, and signal light emitted by the display screen is projected on the imaging lens; and the signal light passes through the imaging lens to form a floating real image which is in mirror symmetry with the display screen in the air. According to the image inquiry equipment, the height and / or inclination of the imaging device are / is suitable for observation of medical staff and operation requirements of floating real images, the physical fatigue of the medical staff is reduced, and the film reading efficiency and accuracy of the medical staff adopting the image inquiry equipment are improved.

A method performed by an electronic device according to one embodiment may include: an operation of obtaining a text query corresponding to an image query output by a trained first model by inputting an image query into a trained first model; an operation of obtaining one or more images as a first search result for an image query and one or more texts as a second search result for a text query from a database; a set of candidate images determined according to the first search result and the second search result; an operation of obtaining a multimodal score for a set of candidate images output by a trained second model by inputting an image query and a text query into a trained second model; and an operation of determining one or more target images from a set of candidate images based on a multimodal score for a set of candidate images.

The application provides an image detection method and device, electronic equipment and storage medium, comprising: collecting an image to be processed; using a pre-trained image encoder to extract features of the image to be processed to obtain target image features; inputting training set text features and the target image features into a pre-trained contrast network to perform feature matching calculation to obtain a target image query result value; performing similarity calculation on the target image features and training set image features to generate a target similarity matrix; performing nonlinear mapping calculation on labels and the target similarity matrix based on first target hyperparameters to generate a target similarity query result value; performing weighted calculation on the target image query result value and the target similarity query result value based on second target hyperparameters to obtain a target classification result value; and the target classification result value is used to indicate a detection result of the image to be processed. Thus, the application can be more conveniently and quickly applied to various different application environments.

The present application discloses an image query method, device, storage medium and computer program product. The method comprises: determining a first query vector corresponding to an image feature of an image to be queried; performing a query in an image retrieval database based on the first query vector to obtain a first image set; determining a second query vector based on the first image set, and performing a query in an image retrieval database based on the second query vector to obtain a second image set, wherein the second query vector includes: a target class query vector and a confusion class query vector; using a classification model, determining an image in the second image set corresponding to the target class query vector, and obtaining an image query result corresponding to the image to be queried. The present application solves the technical problem that when related technologies retrieve images similar to the query image in an image database, the images provided by the queryer need to be stored in plain text on a cloud server, which may lead to the risk of personal privacy leakage.

The present application provides an image query method, device, and program product, relating to the technical field of image search. The image query method includes: obtaining image materials corresponding to the image to be queried; extracting traditional features and depth features in the image to be queried and the image materials according to a preset scale, and generating fusion features corresponding to the traditional features and depth features; performing feature matching between the image to be queried and the image materials based on the fusion features and the preset scale; and displaying, according to the matching result, a target image in the image materials that matches the image to be queried. The embodiments of the present application can automatically search for a target image in the image materials that matches the image to be queried, the query method is simple and efficient, and it is not easy to miss or make mistakes, effectively improving the accuracy of image query.

The invention discloses an image query method, a vehicle and electronic equipment. The method comprises the steps that to-be-queried input data is obtained, and the input data is used for representing a to-be-queried target object in an open scene; encoding the input data to obtain an initial feature; target features matched with the initial features are inquired in original image sample features corresponding to original image samples and foreground image sample features corresponding to foreground image samples in a database, the original image samples and the foreground image samples have a mapping relation, and the original image samples and the foreground image samples have a mapping relation; the original image sample is used for representing an image taking an image of an open scene sample as a background image sample and taking an image of an object sample as an image sample of a foreground image sample, and the proportion of the size of the object sample in the original image sample is smaller than a set threshold value; and marking or outputting a target image corresponding to the target feature, the target image including the target object. According to the invention, the technical problem of low image query precision is solved.

A query modality recommendation system provides recommendations to use a particular query modality based on one or more categories of search results for a search query. Upon receiving a search query in a first query modality at a search engine, the query modality recommendation system determines to recommend use of a second query modality based on one or more categories of the search results. For example, the first query modality may be a textual query and the second query modality may be an image query. In aspects, recommending use of the second query modality comprises comparing a first search performance of the one or more categories for the first query modality in historical search queries to a second search performance of the one or more categories for the second query modality in the historical search queries.

Systems and methods for unimodal visual search can include obtaining an image query, processing the image query to generate an intent determination, determining a particular prompt based on the intent determination, determining a plurality of search results, and processing the particular prompt, the image query, and at least a subset of the plurality of search results to generate a model-generated response. A generation model can render different responses based on different prompts related to different intents.

The invention provides an image retrieval method and device, equipment, a storage medium and a program product, and is applied to the technical field of image processing. The method comprises the following steps: acquiring an image retrieval data set and an image query data set, wherein the image query data set comprises a plurality of complete images and a plurality of partially missing images; constructing an initial similarity matrix of the image retrieval data set and the image query data set based on a cosine similarity calculation formula; constructing a first target function of a matrix completion problem based on the initial similarity matrix, wherein the first target function is used for solving a target similarity matrix meeting positive semidefinite and low-rank characteristics; solving the first target function, and outputting the target similarity matrix; and outputting an image retrieval result according to the target similarity matrix.

The application discloses a kind of image extraction model construction, image query and video generation method, device, the method includes obtaining all video frame images in video library;Each of all video frame images is carried out encoding processing, and first video frame image encoding sample set is obtained;Each of all video frame images is carried out data enhancement processing, and the image after enhancement is encoded to obtain second video frame image encoding sample set;First video frame image encoding sample set, second video frame image encoding sample set are input into pre-trained image extraction model and are trained, so that image extraction model can accurately extract the feature of video frame, improve the accuracy of video frame image matching.

This invention discloses a multimodal planetary landform semantic retrieval method, system, terminal device, and medium, belonging to the field of semantic retrieval technology. The method includes: acquiring planetary remote sensing images and corresponding original descriptive texts and performing semantic processing to construct an image-text pair dataset; constructing a visual-language model with a two-stream neural network architecture and training it through contrastive learning to achieve alignment of visual and geological semantic features; segmenting the full-scale remote sensing image of the target planet into multi-resolution tiles, extracting feature vectors, and constructing a vector index library with associated geographic coordinates; receiving text and / or image query requests, encoding them into query vectors, matching them against the index library, and outputting the matching results. This invention overcomes the data and semantic gap and closed-set limitations of existing technologies, achieving zero-sample open-vocabulary retrieval and planetary-level second-level response, supporting multimodal queries and process-oriented analysis, and contributing to the discovery of rare landforms and planetary geological science research.