748 results about "Handwriting" patented technology

The invention discloses a writing brush calligraphy practice correction system based on real-time handwriting analysis. The system comprises a sensing layer used for collecting handwriting tracks, physiological signals, environmental parameters and ink mark characteristics; the edge calculation layer is used for executing noise filtering, coordinate system normalization, multi-modal data alignment and feature primary extraction through an Apache Kafka data pipeline; and the algorithm analysis layer is used for carrying out super-long calligraphy stroke sequence modeling by adopting an S4 architecture time sequence model, introducing a Neural ODE module for modeling, capturing dynamic characteristics in a continuous pen wielding process, constructing a multi-physics-field coupled PINN framework, constraining neural network prediction through a physical loss function, deploying a dual-stage characteristic extractor to extract high-order characteristics, and extracting the high-order characteristics. Book style features are extracted, and the current practicing book of the user is classified in real time; the intelligent correction layer is used for generating a dynamic correction suggestion, constructing a personalized learning path, realizing self-adaptive scoring and providing aesthetic dimension feedback at the same time; and the user interaction layer is used for providing an AR correction interface.

The invention belongs to the cross technical field of artificial intelligence and image recognition, and discloses a cursive script image sequence recognition method for modeling by fusing a stroke structure, and the method comprises the steps: preprocessing and normalizing a cursive script image, eliminating interference information, normalizing the form of the cursive script image, and guaranteeing the stability and effectiveness of a subsequent processing flow; based on stroke decomposition and feature coding of structural analysis, stroke-level structural features are extracted through character skeleton modeling, and cursive writing characters are converted into time series data; modeling a cursive script recognition neural network fused with structural semantics, and recognizing a stroke time sequence by adopting a BiLSTM neural network; an identification output and result optimization module is designed to ensure the final identification quality; through application of scene integration and platform deployment interface design, practical deployment of the model and butt joint of a front-end platform are realized, and a complete cursive script recognition ecology is constructed. According to the method, not only is the structured representation capability of the cursive script image improved, but also the recognition precision and generalization performance of the model on complex handwriting are remarkably enhanced.

The invention relates to the technical field of information security, and discloses a handwriting dynamic encryption and electronic signature method based on a national secret algorithm, and the method comprises the steps: obtaining the handwriting data of a user, and carrying out the preprocessing of the data to remove noise and errors; carrying out feature extraction on the preprocessed handwriting data, extracting corresponding track features, speed features and pressure features, and generating a feature hash value of a unique identifier through a cryptographic SM3 hash algorithm; splicing and combining the feature hash value and a user private key, deriving a dynamic key through a national secret SM2 algorithm, and generating an electronic signature by using the dynamic key; an electronic signature is combined with a timestamp to form a structured signature packet, and the signature packet is hierarchically encrypted and stored in a database through a national cryptographic SM4 algorithm. According to the method and the system, the handwritten signature picture, the digital signature technology, the electronic signature technology and the biological recognition and layout file processing technology are fused, so that the safety and the reliability of electronic document signing are improved.

This invention relates to systems and methods for real-time dynamic classification and orchestration of test automation components in distributed DevOps environments. The system features an Auto Identify Automation (AIA) engine that leverages supervised learning, Multi-Modal Artificial Intelligence (AI), and Generative AI technologies. It includes a Smart Scenario Designer interface that allows users to author test scenarios using handwriting and voice inputs, which are processed in real-time by AI-driven handwriting recognition, voice recognition, and Natural Language Processing (NLP). The system dynamically suggests relevant automated components via a smart bubble pane, facilitating rapid scenario creation. The architecture is tool-agnostic and scalable, with a Shared Workbench Engine that supports real-time collaboration and conflict resolution. The system continuously adapts and improves, ensuring that the automation suite remains consistent, up-to-date, and aligned with evolving software requirements, enabling efficient and user-friendly management of complex test automation processes.

The invention provides a handwriting real-time prediction method based on a hybrid time sequence convolutional network. The method comprises the following steps: acquiring real track data of a user in a touch screen writing process; preprocessing the real trajectory data to form a multi-dimensional time sequence feature sequence with a preset length; inputting the multi-dimensional time sequence feature sequence into a trained trajectory point prediction model constructed based on a hybrid time sequence convolutional network, and outputting predicted trajectory coordinates; on the basis of the real trajectory data and the predicted trajectory coordinates, trajectory smoothing processing is carried out, and predicted trajectory data used for drawing is generated; and drawing the predicted trajectory data on the touch screen in real time. According to the method, hardware delay is compensated from the algorithm level, writing chirality and real-time performance are improved, dependence on high-end hardware is reduced through end-to-end optimization, and low-cost and high-simulation-degree paper and pen writing experience is provided for touch equipment.

The invention relates to the technical field of handwriting analysis, and discloses a handwriting analysis method and system based on emotion calculation multi-modal recognition, and the method comprises the steps: obtaining handwriting data of a writer, and obtaining handwriting features through employing a multi-modal collection technology, specifically, dividing a writing process into a plurality of writing time periods according to time, and each time period does not exceed 5 minutes; collecting pen point pressure data by using a pressure sensor, collecting writing speed data by using a speed sensor, and collecting font structure data by using an image sensor; for each section of handwriting, executing a feature extraction strategy, fusing dynamic and static features, and generating a multi-modal feature set; inputting the feature set into a pre-trained emotion calculation model; multi-modal fusion breaks through the limitation of a traditional single mode, handwriting features are comprehensively described through a 200 + index, dynamic and static dimensions are combined, and the comprehensiveness of analysis is improved; the 300 + submodel and the million-level sample library ensure the analysis precision, the deep learning architecture captures feature association, and the generalization ability of the model is enhanced through cross validation and online learning.

The invention relates to the technical field of computer data processing and mode recognition, and discloses an intelligent handwriting record analysis system supporting translation process traceability and capability assessment, which comprises the following steps: collecting multi-dimensional handwriting data generated when a user translates by using an intelligent pen; the Hidden Markov model decodes the handwriting into translation behavior primitive sequences such as smooth writing, hesitant pause and the like; automatically dividing semantic regions such as a main translation region and a draft region by a density clustering algorithm; performing space-time fusion attribution to generate a space-time attribution log for accurately recording behaviors, time and positions; and establishing a multi-dimensional capability index system containing translation efficiency, quality and strategies based on the log, and carrying out quantitative calculation and generating a visual user capability portrait. According to the method, the invisible translation cognition process is converted into traceable and quantifiable objective data, deep insight and comprehensive evaluation of the translation process are achieved, and a scientific and efficient analysis tool is provided for translation teaching and interpreter ability evaluation.

The invention discloses an intelligent paper marking system based on image cutting and recognition, belongs to the technical field of intelligent paper marking, aims at solving the problem that the answer quality of students cannot be comprehensively and accurately evaluated, and comprises an image acquisition module which is used for acquiring test paper images, automatically adjusting scanning parameters according to the size and color mode of test paper, supporting multi-angle scanning and acquiring the test paper images; the image preprocessing module comprises an image enhancement unit, a tilt correction unit and a binarization processing unit and is used for carrying out brightness and contrast adjustment, deblurring, tilt correction and binarization processing on the acquired image; through the image cutting, character recognition and semantic understanding technologies, the answer content, including complex handwritten fonts, altered characters and the like, on test papers in various formats can be accurately recognized, misjudgment caused by non-standard formats or writing problems is avoided, the scoring result is more objective and accurate, and the real answer level of students can be better reflected.

The invention discloses a character recognition method and device for a handwritten image, terminal equipment and a storage medium, and the method comprises the steps: obtaining the handwritten image, and converting the handwritten image into a single-channel gray-scale map; wherein the single-channel grey-scale map is an image with a white background and black characters; performing reverse binarization processing on the single-channel grey-scale map to generate a reverse binarization image with black-matrix white characters; all contours in the reverse binarization image are recognized, and the contour with the largest area serves as a character core area; calculating an amplification coefficient according to the width and height of the reverse binarization image; performing boundary expansion on the character core region according to the amplification coefficient, and performing cutting based on the expanded boundary to obtain a cut image; and performing character recognition according to the clipped image. According to the invention, the character recognition accuracy can be improved.

The utility model relates to the technical field of correction, and discloses a student sitting posture corrector which comprises a learning board, a sleeve column is arranged on the learning board, a supporting column is arranged on the sleeve column, a chest support is fixedly connected to the top of the supporting column, and a liquid crystal handwriting board is arranged on the learning board. The supporting column is inserted into the sleeve column, strip grooves are symmetrically formed in the two side walls of the supporting column, a connecting rod penetrates through the sleeve column and penetrates through the two strip grooves, a button is fixedly connected to one end of the connecting rod, a spring groove is formed in the outer side of the sleeve column, the button is located in the spring groove, the inner side face of the button abuts against a spring, and the other end of the connecting rod is in threaded connection with a limiting disc. The liquid crystal handwriting board is environment-friendly and economical, the liquid crystal handwriting board can be repeatedly used, contents can be clearly seen through one key, paper is not needed, waste of the paper is greatly reduced, and the liquid crystal handwriting board is simple in structure and convenient to disassemble and assemble.

The invention discloses a handwritten medical record OCR recognition system and method based on deep learning. The system comprises an image acquisition and preprocessing module, a text detection and region positioning module, a handwritten character recognition module, a semantic correction module and a result storage and export module. The image acquisition and preprocessing module is used for receiving the original medical record image and performing image quality improvement processing to obtain optimized image data; the text detection and region positioning module is used for detecting a text region from the optimized image data and positioning the position information of the text region to obtain text region data; the handwritten character recognition module is used for performing recognition processing on a character sequence in the text region data to obtain an initial text recognition result; the semantic correction module is used for processing the initial text recognition result based on medical priori knowledge to obtain a corrected text recognition result; and the result storage and export module is used for outputting the corrected text recognition result to a target system in a structured format.

The utility model provides a blood collection tube multi-label extension film which comprises a transparent base film with an adhesive layer on the bottom surface, a red emergency treatment mark is arranged at the top of the surface of the transparent base film, a non-transparent protective film covers the surface of the red emergency treatment mark, and the left side or the right side of the transparent base film is connected with an extension part. The left side or the right side of the transparent base film is detachably connected with a transparent expansion wing through an extending part, N + 1 rows of standard label positions are preset on the back face or the surface of the transparent expansion wing, N rows of standard label positions and a row of handwriting areas are correspondingly preset on the surface or the back face of the transparent expansion wing, and the handwriting areas are located below the last row of standard label positions. A matte coating is arranged on the surface of the handwriting area, N is a positive integer larger than or equal to 2, and a weak adhesive layer with the adhesive strength smaller than that of the adhesive layer on the bottom face of the transparent base film is arranged on the standard label position face. Elastic adjustment of the label capacity is achieved through the transparent expansion wings, handwriting input is met, and the red emergency treatment identification is arranged at the top of the surface of the transparent base film and is easy to recognize and not prone to falling off.

A handwriting system including a teaching device and a practicing device is provided. The teaching device is communicatively connected to a network and displays a setup interface which includes a setup window for obtaining practice settings. These practice settings are then transmitted to the network. The practicing device is communicatively connected to the network and displays a user interface for obtaining handwriting information which is transmitted to the network. The practicing device receives an inspection result from the network and displays a feedback message according to the inspection result. A handwriting method and a non-transitory processing device-readable medium are also disclosed.

The invention relates to the field of character and image recognition, in particular to a multi-mode intelligent dictation and correction system and method based on dynamic calibration, and the system comprises an acquisition module for obtaining a writing test image based on voice feedback and carrying out character recognition, a feature splitting module for constructing a feature observation group and labeling a structural unit, the layout analysis module selects a recombination structure by sliding a window frame and sets a fuzzy identification tag based on the prior probability of spatial distribution features, and the identification module compares contour features through region mapping to determine difference types. And the calibration module realizes context restoration and dynamic calibration by removing fuzzy blocks, performing mapping comparison with a sample database and replacing contour features. According to the method, the recognition accuracy of complex handwriting such as scribbling and stroke adhesion is improved, and on this basis, the local image content is calibrated through a replacement mechanism based on context restoration, so that the accuracy and reliability of the correction process are improved.

Some embodiments described in this disclosure are directed to facilitating manipulation of handwritten content displayed in a user interface, including deleting a portion of the handwritten content and subsequently reflowing undeleted portions of the handwritten content in the user interface. Some embodiments described in this disclosure are directed to facilitating conversion of handwritten input into handwriting based on a model handwriting. Some embodiments described in this disclosure are directed to pasting stored text on a user interface as handwritten text or font-based text based on the type of input.

The invention relates to a continuous writing track generation method, system and device based on a brain-computer interface and a medium. The method comprises the following steps: acquiring an electroencephalogram signal and a real writing track when a user imaginates writing through electroencephalogram acquisition equipment; extracting neural activity data related to hand writing movement by using a band-pass filter; extracting writing intention spatio-temporal features based on a preset spatio-temporal deep learning network; mapping an initial handwriting coordinate sequence and a pen state signal through a generator network comprising a full connection layer, a convolution time sequence generation layer and a pen state classification layer; calculating the similarity between the trajectory and a real trajectory by means of a discriminator, and generating handwriting and state signals through adversarial training optimization; and dividing stroke segments according to the pen state and sequentially connecting the stroke segments to generate a continuous writing track. By adopting the method, the brain motion intention can be efficiently and accurately decoded into a coherent writing track, and the practicability of a brain-computer interface in writing and interaction application is improved.

The invention discloses a signature handwriting authenticity digital identification method based on multi-modal features, and relates to the technical field of image processing, and the method comprises the following specific steps: 1, obtaining off-line image data and on-line time sequence data of two groups of signatures to be identified, the data preprocessing module carries out standardization processing on the offline image data and the online time sequence data of the signature to be identified to obtain preprocessed offline image data and preprocessed online time sequence data; 2, inputting the preprocessed offline image data into an offline feature extraction network, and extracting and outputting 1024-dimensional offline features; and 3, inputting the preprocessed online time sequence data into an online signature feature extraction network. According to the method, the online features and the offline features of the signature handwriting are fused and combined to form multi-mode signature handwriting digital recognition, the subtle difference of the counterfeited signature handwriting in static structure consistency and dynamic behavior consistency can be effectively captured, and the recognition capability of complex counterfeited means is remarkably improved.

This application belongs to the field of electronic device technology, specifically relating to a stylus and electronic components. This application aims to solve the problem of low positioning accuracy in related styluses. The stylus and electronic components of this application coordinate the positioning of the stylus through a dual electric field link. The motherboard, a first conductive component, a conductive elastic component, a conductive support, and the pen tip constitute the first electric field link, with the pen tip acting as a transmitter to emit a first electric field signal. The motherboard, a second conductive component, and the electric field transmitter constitute the second electric field link, with the electric field transmitter emitting a second electric field signal. The second electric field signal is radiated onto the touchscreen. The touch chip can calculate the distance between the second and first electric field signals in real time. Based on the calculated distance, it calculates the tilt angle or degree of tilt of the stylus relative to the touchscreen, and then corrects the landing position of the pen tip, further improving the accuracy of the pen tip's position displayed on the touchscreen and making the stylus trajectory less prone to deviation during writing.

The application discloses a handwriting pen magnet automatic assembling integrated equipment and a handwriting pen magnet assembling method, which is used for automatically assembling small magnets and large magnets for handwriting pen supports placed on a dividing disc. A first magnet dispensing mechanism, a first magnet assembling mechanism, a second magnet assembling mechanism and a second magnet dispensing mechanism are sequentially arranged around the dividing disc, and the small magnets and the large magnets are assembled for the handwriting pen supports placed on the dividing disc. The dividing disc sequentially carries the handwriting pens to various work stations, and the equipment at each work station works synchronously, so that the accurate assembling process is ensured, the adverse factors in the production process are reduced, and the production efficiency is improved.

The invention provides an ink screen handwritten stroke beautifying method and device, electronic equipment and a storage medium. The beautifying method comprises the steps of obtaining handwritten stroke report data input by a handwriting pen; generating a first handwritten stroke according to the handwritten stroke report data; driving and displaying the first handwritten stroke on the ink screen; beautifying the appearance of the first handwritten stroke according to a first preset rule to obtain a second handwritten stroke, wherein a pixel region corresponding to the second handwritten stroke covers a pixel region corresponding to the first handwritten stroke; and driving and displaying the second handwritten stroke on the ink screen. The handwritten strokes can be beautified and displayed in the handwriting process, beautified display does not need to be carried out after the strokes are completed, and the handwriting beautified display effect of the ink screen is obviously improved.

1. The name of the design product: handwriting board (FK014). 2. The use of the design product: for handwriting board. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

A method of representing a space of handwriting stroke styles includes representing writer-, character- and writer-character-level style variations within a recurrent neural network (RNN) model using decoupled style descriptors (DSD) that model the style variations such that character style variations depend on writer style.

An interactive host for remote real-time video guidance, comprising a box, a placement slot is arranged on the front surface of the box, a handwriting screen is movably connected to the placement slot through a rotating shaft, a display screen is movably connected to the flange on one side of the placement slot through a rotating shaft, the front surface of the handwriting screen corresponds to the surface of the placement slot, an open slot is arranged on the back surface of the handwriting screen, and the open slot corresponds to the surface of the display screen; a camera is fixedly installed on the upper surface of the placement slot, and the camera focus point corresponds to the front surface of the handwriting screen; a processor and a battery are fixedly installed in the box, the battery is electrically connected to the processor, and the processor is electrically connected to the display screen and the camera. The present application overcomes the shortcomings of the prior art, so that doctors can conduct remote medical consultations through the system, thereby saving time and improving the utilization rate and efficiency of medical resources; and real-time teaching can also be realized, and the range of surgical demonstration is also expanded.

The invention provides a handwriting pen connection method and device, electronic equipment and a storage medium, and relates to the technical field of handwriting pens. The method is applied to a handwriting pen, and the handwriting pen is integrated with a passive radio frequency tag. The method comprises the following steps: activating a passive radio frequency tag under the condition that a radio frequency identification signal transmitted by terminal equipment is received; the radio frequency identification signal is used for triggering pairing connection with the handwriting pen; modulating the identity information of the handwriting pen to a radio frequency signal through a passive radio frequency tag to obtain a response request; the response request is sent to the terminal equipment, so that the terminal equipment is in paired connection with the handwriting pen according to the response request; and under the condition that the handwriting pen is in paired connection with the terminal equipment, sending the use data of the handwriting pen to the terminal equipment through a preset transmission mode. The terminal device and the handwriting pen are automatically triggered to be paired and connected through the passive tag, the connection process between the handwriting pen and the terminal device can be reduced, and the connection efficiency between the handwriting pen and the terminal device is improved.

1. The name of the design product: the answering part of the answering application graphical user interface of the electronic device. 2. The use of the design product: an electronic device. 3. The design points of the design product: the interface content expressed by non-dotted lines in the graphical user interface. 4. The picture or photo that best indicates the design points: Design 1 front view. 5. Design 1 is designated as the basic design. 6. The use of the graphical user interface: the product interfaces of Design 1-Design 4 are the answering interfaces of the intelligent body of the electronic device for generating answering content in response to user input operations (voice, handwriting, keyboard input); the local interfaces of Design 1-Design 4 are used to generate display effects of answering content in response to user input operations. 7. Other circumstances that need to be explained: the design of Design 3-Design 4 contains color.

The invention discloses a handwritten content completion method in combination with voice information, a display device and a storage medium. The method comprises the following steps: displaying a writing interface, receiving a writing operation on the writing interface, and displaying a writing track corresponding to the writing operation on the writing interface; collecting voice information in the process of displaying the writing interface; detecting that a content completion mechanism for the target writing track is triggered, and obtaining target voice information collected in a target time period; the target time period at least comprises a writing moment of the target writing track, and the starting moment and the ending moment of the target time period are separated from the writing moment by a first duration and a second duration respectively; the supplementary track or the voice complementation control for the target writing track is displayed on the writing interface, so that the information loss of the target writing track is reduced. Wherein the voice completion control is used for triggering and playing supplementary voice for the target writing track, and the supplementary text and the supplementary voice corresponding to the supplementary track are determined based on the target voice information.

The embodiment of the present application provides a handwriting pen and an electronic device assembly, and relates to the technical field of terminals. The handwriting pen comprises a pen body assembly and a sliding cover assembly. The pen body assembly comprises a head structure section and a tail structure section, the head structure section and the tail structure section are respectively located at two ends of the axial direction of the pen body assembly, and the tail structure section has a grounding portion. The sliding cover assembly is arranged outside the tail structure section, the sliding cover assembly comprises a metal structure, the sliding cover assembly is slidably arranged on the tail structure section through the metal structure, the sliding cover assembly can slide along the axial direction of the pen body assembly between an opening position away from the head structure section and a closing position close to the head structure section, and the metal structure has an electrical connection portion. When the sliding cover assembly is in the closing position, the metal structure is electrically connected with the grounding portion through the electrical connection portion. In this way, the sliding cover assembly of the handwriting pen has high strength and long service life, and the handwriting pen has low failure rate.

To provide an oil-based ink composition for a ball-point pen capable of obtaining good handwriting with good writing feeling even in writing at a high speed or at a high writing pressure while effectively suppressing ink leakage, and hardly causing strike-through, and to provide a ball-point pen.SOLUTION: A ballpoint pen refill for an oil-based ballpoint pen includes an ink reservoir tube, an oil-based ink composition filled in the ink reservoir tube, and a ballpoint pen tip attached to a front end portion of the ink reservoir tube and configured to supply the oil-based ink composition, wherein the oil-based ink composition contains a first phosphoric acid ester which is a polyoxyethylene hydrocarbon phosphoric acid ester having a hydrocarbon group having 4 or more and 17 or less carbon atoms, a second phosphoric acid ester which is a polyoxyethylene hydrocarbon phosphoric acid ester having a hydrocarbon group having 18 or more and 24 or less carbon atoms, water, and a nonionic surfactant.SELECTED DRAWING: Figure 1

The invention discloses a drawing data protection method and a drawing device, and relates to the technical field of drawing data protection. Before screen clearing is executed, current handwriting data are stored, and a right confirmation process is triggered; after receiving a right confirmation success receipt, controlling a display layer to execute screen clearing; if right confirmation fails or is overtime, screen clearing interlocking is kept, and a rollback strategy is executed; by constructing a core mechanism of first storing and then clearing and right confirmation interlocking, the problem of data loss or ownership dispute caused by the fact that the right of drawing data is not confirmed in time before screen clearing operation is effectively solved, high-fidelity and traceable right confirmation protection of the creation process is achieved through combination of handwriting vectorization reconstruction and block chain evidence storage, and the user experience is improved. A father-son hash association mechanism of AI derivative works is introduced, a traceability relationship between original works and generated contents is established on a chain by using a Merkle tree structure, copyright ownership under an AI creation scene is guaranteed, and a hardware-level clear screen interlocking circuit and a system-level family monitoring strategy are matched.

The application discloses a handwriting corner point determination method and device, a storage medium and a terminal, and relates to the technical field of computer image recognition. First, the writing speed of each trajectory point in handwriting and the final curvature of each trajectory point are calculated, and the final curvature is the average of all curvatures of vectors formed by the trajectory point and other trajectory points in a preset range. Then, a trajectory point meeting a condition is selected as a first corner point. Finally, pseudo corner points in the first corner point are removed. Since the average of all curvatures of the trajectory point in the preset range is taken as the final curvature of the trajectory point, that is, the average of the cumulative curvatures of the sliding window is taken as the curvature of the window center trajectory point, the misleading of curvature mutation to corner point selection is reduced, the curvature mutation can be effectively smoothed, more accurate corner points can be selected, line segment fitting of handwriting is performed, pseudo corner points in the first corner point are removed, the pseudo corner points in the corner points can be effectively removed, and finally, correct corner points in the handwriting are determined.