234 results about "Glyph" patented technology

The invention relates to a Lao image text recognition method and device fused with a language error correction model, and belongs to the field of natural language processing. Lao character structures are more complex and have numerous homomorphic words, and the method is provided in order to solve the problem that similar characters in Lao images are poor in recognition. The Lao text image recognition method comprises the steps of Lao text image data set construction, Lao image text recognition model construction fused with a language error correction model, Lao image text recognition model training fused with the language error correction model and Lao text image recognition. The Lao image text recognition device fused with the language error correction model is manufactured according to functional modularization of the four parts, and the problem that Lao characters are difficult to recognize due to similar font structures is effectively solved.

An end-to-end rendering system enforces policy-constrained, symbolic presentation of artificial-intelligence (AI) outputs prior to any pixel emission. An AI accelerator emits inference tokens as (token identifier, confidence, domain tag) tuples into an output FIFO. A graphics processor with a command processor and SIMD co-processor executes a policy engine that runs a deterministic finite automaton (DFA) stored in non-transitory memory. The DFA consumes the tuples and produces, before any frame-buffer writes, a permit / deny decision and a visibility mask that constrain presentation attributes. A glyph selector maps permitted tuples to entries in a constrained glyph dictionary specifying a glyph identifier, semantic class, and allowed substitutions. A provenance tagger computes a cryptographic hash over at least the glyph identifier, a DFA-state policy identifier, a session nonce, and a checksum of the tuples to create an evidence capsule bound to the glyph. A device-aware renderer, consulting a device profile registry and a rendering grammar, emits a renderable asset for the glyph only when permitted by the visibility mask and grammar. A justification ledger records, for each displayed glyph, the evidence capsule and a monotonic timestamp. Executed entirely within the graphics processor, the pipeline prevents unauthorized tokens from entering the display path, enables cryptographically verifiable traceability of visible content, and reduces bandwidth by representing outputs as glyph identifiers rather than text or raster imagery, while allowing runtime policy updates without modifying the underlying inference model.

The embodiment of the invention provides an image editing and model training method and device, a storage medium and a program product. In the embodiment of the invention, an image-text editing model is provided, image editing is carried out on a target text area of an original image from a font dimension and a style dimension, guarantee is provided for the accuracy of image editing through text coding features and character morphological features in the font dimension, and the consistency with a background is kept; in the style dimension, by injecting text style features, the original image style and additional styles are kept, and the availability rate of image editing is improved. Image editing is carried out from the two dimensions of font and style, and the image quality of the obtained image can be improved. Furthermore, in the layout dimension and model training process, local and transverse and longitudinal modification of various alignment modes is supported through a layout loss function and adaptive learning layout information, and the image quality is further improved.

Methods, computer systems, computer-storage media, and graphical user interfaces are provided for automated propagation of glyph edits to corresponding adornments. In embodiments, an indication to attach an adornment to a glyph associated with a variable font is identified. Thereafter, an anchor point indicating a point of attachment of the adornment to the glyph is identified. Based on obtaining an indication to modify a variable font property associated with the glyph, an edit to apply to the adornment is determined. Generally, the edit maintains an alignment of the adornment with a modified anchor point reflecting the modified variable font property associated with the glyph. Thereafter, the edit is applied to the adornment.

The invention belongs to the field of intelligent man-machine interaction, and relates to an intelligent writing and correcting method and system.The method comprises the steps that a flexible pressure sensor matrix and a coordinate positioning system are used for sensing multi-dimensional data generated when an input pen writes, and a four-dimensional writing feature space is constructed; a three-level correction system is adopted, and logical reasoning verification is conducted on the answers through a deep semantic understanding model; the three-stage correction system sequentially comprises OCR font matching, semantic correction based on a large language model and intelligent correction based on a process reward model; a cognitive diagnosis model is introduced, and the answer hesitation degree is judged by analyzing answer indexes; fusing question answering information, utilizing a large model to identify knowledge points to which questions belong, and inferring knowledge mastering weak points according to question answering conditions; writing information is accurately collected through an intelligent writing capture technology based on multi-modal sensing fusion, an intelligent correction integrated method is built in combination with a cognitive diagnosis model, and efficient recognition and accurate correction of written content are achieved.

Embodiments are disclosed for identifying and modifying overlapping glyphs in a text layout. A method of identifying and modifying overlapping glyphs includes detecting a plurality of overlapping glyphs in a text layout, modifying a geometry of one or more of the overlapping glyphs based on an aesthetic score, updating a rendering tree based on the modified geometry of the one or more overlapping glyphs, and rendering the text layout using the rendering tree.

The embodiment of the invention provides an image generation method and device, and the method comprises the steps: obtaining a wordart description text, a target content text and a condition image, and enabling the condition image to be used for constraining the font of a target wordart; based on the wordart description text, processing the condition image to generate a target wordart image corresponding to the condition image; and generating a target image corresponding to the target content text based on the target content text and the target wordart image. According to the method, perfect fusion of the wordart and the content is realized, the aesthetic property and expressive power of the image are improved, the creation threshold of the user is reduced, the image generation process is more efficient and intelligent, and diversified creative requirements are met.

This invention relates to the field of text processing technology, and in particular to a method, device, and medium for processing navigational notice text based on semantic enhancement. The method includes: first, acquiring a content carrier to be processed; then, acquiring the semantic vector and glyph feature vector of the content carrier; concatenating the two types of vectors to form an enhanced text representation; extracting temporal features from the enhanced text representation to obtain temporal features containing forward and backward logical relationships within the text; acquiring the weights of words and sentences in the temporal features and performing weighting to obtain weighted word representations and weighted sentence representations; performing correction processing on the weighted representations to generate corrected text; and finally, validating the corrected text and outputting the target text. This invention can improve the accuracy and efficiency of content carrier processing.

The invention belongs to the technical field of character pattern recognition, and particularly provides an oracle structure recognition method of a font pattern isomorphic network, which comprises three stages of font pattern structure feature extraction, font pattern isomorphic network model and oracle font structure recognition. Through oracle font skeleton extraction, oracle font skeleton singular point detection, skeleton burr and bifurcation optimization, and key point extraction as a node communication path as an edge, an oracle font graph structure is established, and graph structure nodes, edges and graph level features are calculated. The font graph isomorphic network integrates the advantages of a graph isomorphic network and dynamic edge and graph embedding, and learns vector representation of multi-level features such as nodes, edges and graphs of the oracle font graph structure so as to train and identify the font structure of the oracle. The method can be used for structure matching recognition of oracle character pattern images, has the advantage of being high in recognition accuracy, and is suitable for recognition of character pattern structures such as gold texts and seal scripts and recognition of social networks, biological information and molecular structures.

The invention discloses a stylized visual text editing method, a stylized visual text editing system, stylized visual text editing equipment and a storage medium, which are corresponding schemes, and the related schemes aim to solve the problem of style consistency existing in image text editing of an existing diffusion model, and the stylized visual text editing efficiency is improved by combining visual features of a font image and an input text image. The method comprises the following steps of: extracting style embedded information from a text image, and inputting the style embedded information as an enhanced style condition into a diffusion model to realize fine control on a diffusion process, so that the diffusion model can generate a text image with high readability and style consistency, and can realize maintenance of an original text style or style migration based on a reference image.

The invention provides a teaching document anti-copy protection method and system based on OCR interference resistance, and belongs to the technical field of information security and digital copyright protection. According to the method, anti-OCR font processing is applied to document characters, invisible disturbance symbols are inserted between characters or paragraphs, watermark information is embedded in document typesetting or font strokes, and finally a standard PDF or DOCX file is compiled. Watermark information is embedded through stroke thickness change, paragraph row spacing indentation perturbation and other modes. The system comprises a font disturbance module, a character disturbance module, a watermark embedding module, a compiling output module and a verification module. According to the method, the human eyes can normally read the document, but messy codes or disorder can occur when the OCR tool extracts the document, and the document cannot be directly reused; meanwhile, watermark information cannot be stripped, so that leakage tracking is facilitated; and the output file keeps a standard format and is compatible with the existing office teaching process. The method is suitable for anti-copying protection of teaching documents, scientific research data, test papers, contract files and the like.

The embodiment of the invention provides a text error correction method, a text error correction device, electronic equipment and a medium, and belongs to the technical field of financial science and technology. The method comprises the following steps: inputting a target text into a text error detection model for text error detection to obtain text marking data, wherein the text marking data is used for marking correct characters and error characters in text characters; inputting the target text into a text error correction model based on the text marking data; extracting text character and pronunciation features of the text characters based on a character and pronunciation feature extraction sub-model; extracting text font features based on the font feature extraction sub-model, wherein the text font features comprise first mask features of error characters; extracting text semantic features based on the semantic feature extraction sub-model, wherein the text font features comprise second mask features of error characters; and performing text prediction on the text character pronunciation features, the text font features and the text semantic features based on the error correction sub-model to obtain a target error correction text. According to the embodiment of the invention, the error correction accuracy of the text can be improved.

The invention discloses a character string fuzzy matching method and system, and relates to the field of character recognition, and the method comprises the steps: obtaining a plurality of characters of different font sizes and fonts, and constructing a font similarity matrix; in the replacement operation in the distance editing method, character similarity weighting is carried out on the cost of the replacement operation so as to construct a weighted distance editing method; a weighted editing distance is used for the two character strings to be matched, the obtained weighted editing distance is normalized, and the similarity of the two character strings to be matched is obtained; when the similarity is 1, the matching is successful; when the similarity is greater than a set similarity threshold value and less than 1, representing a suspicious matching result; when the similarity is smaller than a set similarity threshold value, the matching fails. The method can solve the problem that character errors exist in similar results recognized by the OCR technology.

The invention discloses a short message identification method and device, a nonvolatile storage medium and electronic equipment. The method comprises the following steps: acquiring a short message to be identified; a pre-trained short message classifier is adopted to perform feature extraction on the to-be-recognized short message to obtain multi-dimensional features, the multi-dimensional features at least comprise one of font features, pinyin features and semantic features, the font features are used for representing structures of characters in the to-be-recognized short message, the pinyin features are used for representing pronunciation of the characters in the recognized short message, and the semantic features are used for representing semantic features of the characters in the recognized short message; the semantic features are used for representing the meaning of the to-be-recognized short message; fusing the multi-dimensional features to obtain fused features; and identifying the fusion features by adopting a short message classifier to obtain the type of the short message to be identified. The technical problem that the short message recognition accuracy is low is solved.

The invention relates to the technical field of image detection, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses a Chinese character font generation method, device, equipment and medium, the method comprises the following steps: obtaining a Chinese character image to be processed, and carrying out image coding on the Chinese character image to be processed to obtain a Chinese character image sequence; performing style feature extraction and semantic feature extraction on each Chinese character image vector in the Chinese character image sequence to obtain corresponding Chinese character style features and Chinese character semantic features; constructing a corresponding style loss function and a semantic loss function according to the Chinese character style features and the Chinese character semantic features; performing loss weighting calculation on the style loss function and the semantic loss function to obtain a target loss function; and performing font style generation on the to-be-processed Chinese character image according to the target loss function to obtain a target Chinese character font of the to-be-processed Chinese character image. The Chinese character font generation efficiency and font generation diversity can be improved.

The invention relates to the technical field of artificial intelligence and finance, and provides an artificial intelligence-based text wordart method, device, equipment and medium, on one hand, a target text is rasterized based on a text wordart model to obtain a target raster image text, a vector text layer is converted into a pixel layer, and the pixel layer is converted into a pixel layer; the text is not limited by language types, the problem that the Chinese language structure is complex is avoided, and the text-to-graph problem is converted into the graph-to-graph problem; on one hand, a large language model is used for recognizing regional coordinates used for semantization in raster image characters and expanding style cue words, and the controllability degree of text art generation is improved; and on the other hand, the discriminator is utilized to guide the diffusion model to generate a font which can be obviously recognized, and meanwhile, through an adversarial training mechanism, the generated wordart has the advantages of clear font recognition and artistic semantic change, so that the style and the font are highly fused and balanced, and the problems of low efficiency and poor quality of the text wordart are solved.

A B2B platform-based prohibited word auditing system specifically comprises the following steps: step 1, preliminary prohibited word detection: firstly, the system performs preliminary prohibited word detection on a text submitted by a user, and updates a prohibited word library at the same time; 2, anagrams are detected, wherein after prohibited words pass detection, the text is sent into a special anagrams detection module to be further processed; and in the deformed word detection module, the text is subjected to alphabetic processing, and more complex font and symbol deformation matching is carried out, so that all potential prohibited behaviors can be identified, and meanwhile, a prohibited word bank is updated. According to the method, multi-level prohibited word management is adopted, the multi-level management allows the system to carry out distinguishing and processing according to the severity of the content, different weight and priority settings are provided, the accuracy and flexibility of detection are improved, different degrees of illegal content can be effectively coped with, and misinformation and missing report are reduced.

Text display method, compilation method and related equipment. In this method, a lightweight device can use the serial number of the first static text to be displayed to find the corresponding first glyph index set that has been shaped, and use the first glyph index set to search the glyph index font library to obtain the correct first glyph set that has been shaped for the string of the first static text, and then the first glyph set can be directly displayed. When the technical solution provided by the present application is implemented, the lightweight device does not need to shape the text of the complex language during operation, and the glyphs of the complex language can be correctly displayed, thereby improving the lightweight device's ability to support complex languages.

Embodiments of the present disclosure provide a method, an apparatus and an electronic device for determining a word representation vector, and a computer-readable storage medium, which belong to a field of processing natural languages. The method includes obtaining a set of glyph units of a text; obtaining a context vector of the text based on the set of glyph units; and predicting next word of the text based on the context vector. The method for determining the word representation vector of the present disclosure can effectively obtain a corresponding set of glyph units even for hieroglyphics in which hyperbolic characters are prone to appear or languages evolved from the hieroglyphics, thereby improving an accuracy of determining the word representation vector.

According to one aspect, the subject matter described herein includes a method for extracting text from unstructured documents. The method includes receiving a page of an unstructured document; extracting, from the page, a glyph identifier and a glyph position for each glyph on the page; and generating an adjacency graph based on the glyph positions for each glyph on the page, each node in the graph corresponding to a glyph and comprising glyph information that includes at least the glyph identifier and the glyph position for the respective glyph. The method further includes processing the adjacency graph by a machine learning model to classify edges and nodes in the adjacency graph, then grouping the glyphs according to their edge and node classifications to produce text output.

The invention discloses a ViT-based automatic detection and recognition system and method for Manchu ancient book characters, and belongs to the technical field of artificial intelligence and digital literature protection. The system comprises a YOLO target detection module, a positioning network module, a ViT module and a classifier module. The YOLO target detection module is used for identifying and positioning each individual character area in the whole Manchu ancient book image, the positioning network module is used for automatically adjusting the position, the rotation angle and the scaling of the character image, and the ViT module is used for extracting the deep feature of the character image and modeling the character visual representation. And the classifier module is used for mapping the feature vectors output by the ViT module into specific character tags and splicing the specific character tags into a transcription text. The invention provides an end-to-end intelligent processing system, solves the problems of character pattern diversity, image noise, multi-language mixing and the like of Manchu literatures, and realizes high-precision identification of Manchu characters and intelligent sorting and translation of Manchu and Chinese bilingual literatures.

The invention provides a color image encryption method based on a hyper-chaotic system and a go rule, which comprises the following steps of: obtaining an initial value by a plaintext image and four external keys, and combining the external keys to obtain four chaotic sequences; a chaos sequence is combined with a go rule to obtain position coordinates, and pixel points of three image channels of the plaintext image are rearranged according to the position coordinates to obtain an image matrix P1; the image channel sequence of the image matrix P1 is determined according to the three chaotic sequences, the zigzag extraction starting point of each image channel and the zigzag extraction sequence of the two-dimensional plane selected by the external secret key are reconstructed today by day, and an image matrix P2 is obtained; performing three-dimensional zigzag extraction to obtain an image sequence; bidirectional diffusion of the image sequence is realized by three chaotic sequences; and re-putting according to a three-dimensional zigzag extraction sequence to obtain a ciphertext image. The color image encryption method can effectively resist violent attacks, statistical analysis attacks and differential attacks, has good robustness, and is suitable for color image encryption with high security requirements.

The invention relates to an image coding model training method and device, computer equipment and a storage medium. The method comprises the following steps: collecting sample images of a plurality of handwritten signatures; extracting a main body area image of the handwritten signature from the sample image, and performing data enhancement processing on the main body area image to obtain an enhanced image of the handwritten signature; inputting the enhanced image as a guide condition of an image generation process into a diffusion model, and enabling the diffusion model to output a generated image corresponding to the handwritten signature as a training data set; and carrying out model training on a preset base model by using the training data set by adopting a comparative learning method to obtain an image coding model. By adopting the method, the model can have relatively high anti-interference capability on external factors such as color font jitter and background texture change of the signature image, and the attention on the signature font structure characteristics is enhanced, so that the robustness of image coding is improved.

Methods, system, and apparatus, including computer programs encoded on a computer storage medium. for generating fonts. In one aspect. a method comprises generating glyphs for one or more fonts using an adaptive refiner model.

The invention relates to an oracle denoising method and device based on channel attention and font aggregation, and a medium. The method comprises the following steps: obtaining an oracle image containing noise; the oracle bone image is input into a denoising model, the denoised oracle bone image and a character skeleton are output, the denoising model comprises an input mapper, an output mapper, an ECharFormer module and a font corrector, the input image is converted into shallow layer features through the input mapper, the shallow layer features are converted into reconstruction features and font features through the ECharFormer module, and the reconstruction features and the font features are reconstructed through the output mapper. The reconstruction features are converted into denoised oracle images through an output mapper and output, and the font features are converted into character skeletons through a font corrector and output. Compared with the prior art, the method can achieve a rapid and good denoising effect while keeping the oracle alphabet fonts.

The invention relates to the technical field of writing error recognition, and discloses a Chinese writing error intelligent recognition method and system based on a deep neural network, and the method comprises the following steps: 1, obtaining a target single Chinese character image after binarization processing, and obtaining a normalized binary font image; 2, skeleton extraction and node labeling are carried out on the normalized image, and a font topological graph is constructed; 3, determining a structure normal form label based on the topological graph and image projection, and dividing parts to obtain an outer surrounding region, an inner part region, left and right parts and intersection information; step 4, calculating consistency measurement of surrounding, left-right and cross structures; step 5, obtaining a corresponding standard measure in combination with the standard font of the target Chinese character, setting a fixed tolerance to form a standard parameter interval, and generating a structural feature vector; and step 6, outputting a writing error recognition result according to the deep neural network model. According to the invention, automatic identification and error type determination of Chinese writing structural errors are realized.

The invention discloses an intelligent font generation method and device based on a generative adversarial network and font skeleton transformation, and the method comprises the steps: obtaining a source font image and a style font image, inputting the source font image into a font skeleton extraction algorithm based on a maximum inscribed circle rule and a connectivity criterion, and carrying out the extraction to obtain a font skeleton image; a cyclic generative adversarial network composed of a font generator and a discriminator is constructed, the discriminator comprises a content discriminator and a style discriminator, the cyclic generative adversarial network is trained to obtain a trained font generator and a trained discriminator, the font generator comprises a content encoder, a style encoder and an image restoration decoder, and the trained discriminator comprises a content encoder, a style encoder and an image restoration decoder. And inputting the font skeleton image and the style font image into a trained font generator to obtain a generated font image. Through the generative adversarial network and the font skeleton transformation technology, the limitation of sample scarcity is overcome, and high-quality calligraphy fonts meeting specific structure and style requirements are generated.

The utility model relates to the technical field of plastic trays, and discloses an integrated shared tray with a matts-shaped bottom, which comprises an upper plate surface, the matts-shaped bottom and bottom feet, the upper plate surface, the matts-shaped bottom and the bottom feet are integrally formed, the lower end of the upper plate surface is connected with the bottom feet, the bottom feet are connected with the matts-shaped bottom, and the upper plate surface is connected with the upper plate surface. The plane of the upper plate face is composed of a grid formed by a plane shaped like a Chinese character'ri 'and block-shaped reinforcing ribs, the bottom face of each block-shaped reinforcing rib is an inclined face, a fork inlet assembly is fixedly arranged at the front end of the bottom shaped like the Chinese character'tian', sharp-angled edges are fixedly arranged at the inner end of the bottom shaped like the Chinese character'tian ', and oblique angles are arranged on cross beams of the bottom shaped like the Chinese character'tian'. According to the integrated shared tray with the bottom shaped like the Chinese character'tian ', the upper plate face is designed to be the large plane, enough space is guaranteed to prevent goods of various shapes and sizes, meanwhile, the large plane is assembled with the anti-skid plane, optimization treatment is conducted, and the purposes of skid resistance, durability, easy cleaning and the like are achieved so as to adapt to different environments and use scenes.

The invention relates to the technical field of artificial intelligence, can be applied to the medical field and the financial science and technology field, and discloses a font generation method and device based on a tensor high-order coupling layer, equipment and a medium, which are applied to a dynamic financial document generation system or an automatic labeling scene of a medical image report. The method comprises the following steps: acquiring font style descriptors and font structure data, and preprocessing the font style descriptors and the font structure data to generate standardized font style descriptors and font structure embedding; performing feature extraction and dynamic parameter generation processing on the standardized style descriptors to generate style factors; obtaining a data segmentation vector, and performing multi-rank tensor decomposition on the data segmentation vector based on the style factor to obtain a transformation feature; adjusting the coupling strength between different attributes of the transformation features to generate features after gating optimization; and embedding the gated optimized features and the font structure for feature fusion and feature decoding to generate a target font image. The method has the advantages that the generated fonts are high in visual quality and rich in style diversity.

The invention relates to the technical field of intelligent decision making, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses a character font generation method, device, equipment and medium based on feature extraction. Obtaining font initial features; performing multi-level feature refinement processing on the font initial features to obtain font refinement features; performing style consistency processing on the font refinement features to obtain style consistency features; calculating predicted fonts according to the style uniformization features, and calculating a multi-dimensional loss function of the character font data set according to the predicted fonts; and performing parameter optimization on the pre-constructed font generation model according to the multi-dimensional loss function to obtain a target font generation model, and performing font generation by using the target font generation model.