110results about How to "Clear boundaries" patented technology

The invention relates to the technical field of image processing, in particular to a training method and system based on a circuit board defect detection model. The method comprises the following steps: acquiring an automatic optical monitoring image of the circuit board, and carrying out circuit board surface defect detection on the automatic optical monitoring image of the circuit board so as to obtain surface defect data of the circuit board; marking a circuit board defect area according to the circuit board surface defect data so as to obtain circuit board defect area data; carrying out welding spot three-dimensional contour imaging according to the automatic optical monitoring image of the circuit board so as to obtain welding spot three-dimensional contour data, and carrying out circuit board pseudo soldering analysis according to the welding spot three-dimensional contour data so as to obtain circuit board pseudo soldering data; and performing electrical connection defect analysis according to the circuit board defect area data so as to obtain electrical connection defect data. Based on the computer vision technology, the accuracy of the circuit board defect detection model is improved.

The invention relates to a focused ion beam ultrathin section sample preparation pretreatment method for a wafer sample, and belongs to the technical field of wafer material microscopic experiments. The wafer sample preparation pretreatment method provided by the invention comprises the following steps: (1) depositing a metal oxide on the surface of a wafer sample by adopting an atomic layer deposition technology to obtain an ALD layer; (2) coating a curing glue solution on the surface of the ALD layer, and curing to obtain a curing glue layer; and (3) plating a conductive protection layer on the surface of the cured adhesive layer to finish sample preparation pretreatment. The sample preparation pretreatment method disclosed by the invention can well solve the problems of irradiation damage and deformation of a fine structure which is not resistant to electron beam irradiation, curtain effect in a cutting process, unobvious structural boundary in a shooting process and the like in focused ion beam ultrathin section sample preparation, and has good application prospects in the technical field of wafer material microscopic experiments. And the practical value is very high.

The invention belongs to the technical field of remote sensing detection, and particularly discloses a photovoltaic station fine identification method and device based on a classifier and deep learning, and the method comprises the steps: carrying out the preprocessing of a multi-source remote sensing image of a to-be-identified photovoltaic station in a research region range; inputting the preprocessed multi-source remote sensing image into a trained machine learning classifier to carry out preliminary coarse resolution recognition, and obtaining a high-resolution remote sensing image containing a coarse recognition contour of a potential photovoltaic region; and inputting the high-resolution remote sensing image containing the coarse identification contour of the potential photovoltaic region into a trained deep learning model for fine identification, and outputting a segmentation mask with panel type information, the segmentation mask being used for distinguishing a photovoltaic panel and a panel gap. According to the method, the potential area of the photovoltaic station can be quickly positioned in the specified area range, and fine identification is carried out on the basis, so that the accuracy and efficiency of identifying the photovoltaic station in a complex and diversified area are improved.

The invention provides a logistics policy file analysis method based on multi-modal features, which comprises the following steps of: extracting key words of themes from a logistics policy file, and performing importance score sorting on the key words to obtain the sorted key words, so as to clarify the boundary of the key words; furthermore, by means of a timestamp marking mode, multi-modal keywords fusing time sequence features are obtained, a more accurate prediction effect is achieved, and a foundation is further laid for subsequent evaluation of logistics policy documents according to time periods. In addition, similarity evaluation is carried out on the superior logistics policy file and the subordinate logistics policy file through a similarity function, and the superior and subordinate collaboration degree is obtained to evaluate the implementation efficiency of the logistics policy file. In addition, in the process of obtaining the superior policy document, a more accurate keyword of the theme is obtained by adjusting the preset weight of the theme at the subtitle.

The invention relates to the technical field of remote sensing image processing, and discloses a remote sensing ground feature classification extraction network and drawing method in a complex scene, and the method comprises the following steps: S1, obtaining high-resolution satellite remote sensing image data, carrying out the preprocessing of an image, and generating a multi-scene ground feature data set; s2, constructing a two-layer U-shaped network comprising an encoder and a decoder, wherein the two-layer U-shaped network is used for multi-scale feature extraction and ground feature boundary segmentation; s3, inputting the preprocessed remote sensing image into a two-layer U-shaped network, and carrying out ground feature classification and segmentation; s4, performing splicing processing on the segmentation result, and generating a ground feature type spatial distribution map; and S5, performing noise elimination and post-processing operation on the generated distribution map. The multi-scale features are selectively extracted through the feature selection module (FSM), the attention of the network to small target ground features can be enhanced, and the segmentation precision of the small-scale ground features is remarkably improved by selecting the features containing important details.

The invention provides a shale pore type identification method based on a digital core, and the method comprises the steps: carrying out the gray adjustment processing and image noise reduction processing of an original gray image of a to-be-identified shale sample, and obtaining a standard gray image; organic matter and transition zone images in the standard grayscale image are extracted, organic matter identification processing is carried out, and an organic matter connected body image is determined; extracting a pore image in the standard gray-scale image, performing pore recognition processing in combination with the organic matter connected body image, and determining an organic pore image and an inorganic pore image; and performing micro-crack identification processing on the inorganic pore image, and determining a micro-crack image and an inorganic pore image. By applying the method, the organic pores, the inorganic pores and the microcracks of the shale can be quantitatively identified, the pore structure of the shale can be quantitatively represented, and the structural parameters of the organic pores, the inorganic pores and the microcracks can be analyzed.

The invention relates to the technical field of winnowing and removing devices, in particular to a wizened snakegourd seed winnowing and removing device which comprises a processing platform, a winnowing and removing mechanism used for separating wizened snakegourd seeds is arranged on the processing platform, and a batch feeding mechanism is arranged in the winnowing and removing mechanism. A winnowing auxiliary mechanism for separating the separated wizened snakegourd seeds is arranged below the winnowing removing mechanism, a rapid discharging mechanism is arranged on the processing platform, the winnowing removing mechanism comprises an air conveying pipeline fixedly installed on the processing platform, and the upper end of the air conveying pipeline is communicated with an air injection disc. According to the snakegourd seed winnowing and removing device, the winnowing and removing mechanism is arranged, the snakegourd seeds can evenly fall down in a rotating mode through mutual cooperation between the rotary feeding assembly and the material guiding inclined plate, the snakegourd seeds can be effectively prevented from being mutually shielded and overlapped in the falling process, and therefore the snakegourd seed winnowing and screening effect is improved; and local accumulation of the snakegourd seeds on the processing platform can be avoided.

The present application relates to a sample analyzer, a sample analysis method and a sample analysis system, including: obtaining the original data corresponding to the sample, the original data including at least one of the original light signal data and the original scatter plot; the original light signal data including at least two paths of light signal data with different angles; inputting the original data into a conversion model, the conversion model including N conversion layers connected in sequence, each conversion layer being used to convert the light signal data according to the corresponding conversion function to obtain converted light signal data; wherein the input of the first conversion layer of the conversion model is the original light signal data, and the input of the Mth conversion layer of the conversion model is the light signal data converted by the M-1th conversion layer; N is greater than or equal to 2, and the maximum value of M is N; generating a converted scatter plot based on the converted light signal data of the Nth conversion layer of the conversion model, and identifying the scatter plot to obtain a particle classification result. This method can improve the accuracy of particle classification.

The invention discloses a dialogue intention analysis method and device, equipment, a storage medium and a program product, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining at least one dialogue statement sequence, and carrying out the intention classification analysis of dialogue statements in the at least one dialogue statement sequence, obtaining each type of intention and at least one dialogue statement classified into each type of intention; based on the time sequence of each dialogue statement in the corresponding dialogue statement sequence and the class intention corresponding to each dialogue statement, determining a jump relationship between different class intentions; according to the jump relation between the different types of intentions, an intention relation graph is constructed, the intention relation graph comprises a plurality of nodes and a plurality of directed edges, the nodes represent the types of intentions, and the directed edges represent the jump relation between the different types of intentions; and generating an intention analysis result based on the intention relation graph. The dialogue intention analysis efficiency can be improved.

The invention discloses an image processing method, a model training method and electronic equipment, and relates to the field of large model technology and image processing. The method comprises the steps that an image to be processed is acquired, and the image to be processed comprises a target object; performing feature extraction on the to-be-processed image by using a feature extraction model to obtain article features of the target article; and based on the article features and the edge information of the target article, guiding an image generation model to carry out conversion processing on the to-be-processed image to obtain a target image, other regions except the region where the target article is located in the target image being displayed through a preset texture, and the target article in the target image being in a preset state. The technical problem that the image processing effect is poor in the prior art is solved.

The invention discloses rotary batch epitaxy equipment, which comprises a wafer loading system, an equipment front-end module, a wafer left vacuum chamber, a wafer right vacuum chamber, a wafer transfer chamber, a plasma etching cavity, a heating volatilization cavity, a right reaction module and a left reaction module, and is characterized in that the wafer loading system is used for placing wafer boxes, and 25 wafers are loaded in each wafer box; a manipulator in the equipment front-end module takes out wafers in a wafer box on the wafer loading system, carries the wafers to a wafer left vacuum chamber and a wafer right vacuum chamber after calibration and positioning, a manipulator in the wafer transfer chamber can grab the wafers in the wafer vacuum chambers, loads the single wafers and conveys the single wafers to a subsequent reaction chamber, and the wafer transfer chamber can transfer the single wafers to the subsequent reaction chamber. Selective epitaxy is carried out firstly, then full epitaxy is carried out, a, adhesion and fracture between a wafer boat and a wafer are avoided, and b, the epitaxy temperature is reduced, the growth time is shortened, the boundary of Si and SiGe layers is clear, and the electrical performance of the chip is improved.

The invention discloses a preparation method of monodisperse vaterite-shaped calcium carbonate with uniform particle size, which comprises the following steps: 1, mixing lime with an ethanol solution, carrying out digestion reaction, and standing and settling lime slurry after the digestion reaction is finished; 2, carbon dioxide gas is introduced into the lime slurry for a carbonization reaction, vaterite-shaped calcium carbonate is generated, and different composite crystal growth inhibitors are added during carbonization to regulate and control the crystal form of calcium carbonate; and 3, after the carbonization reaction is finished, carrying out suction filtration, drying and crushing to finally obtain the monodisperse vaterite-shaped calcium carbonate with uniform particle size. The raw materials are low in obtaining cost, the preparation process is simple and easy to adjust, the calcium carbonate particles are regular in morphology and uniform in particle size distribution and are monodisperse products, the method for preparing the calcium carbonate with the special morphology is widened, and the prepared vaterite-shaped calcium carbonate is expected to be applied to the special fields such as the food industry and the pharmaceutical industry.

The invention relates to the technical field of optical coating, in particular to a partitioned coating method for a spatial extreme ultraviolet band reflector, which aims to coat different or same films on more than two or more regions at certain intervals. The method comprises the following steps: firstly, designing more than two or more EUV wave band multilayer films, wherein the structures and the central wavelengths of the EUV multilayer films can be different; then designing an adjustable shielding coating tool which is in direct contact with the mirror surface of the reflecting mirror; the EUV wave band is plated on the surface of the cleaned reflecting mirror in a regional mode through an adjustable shielding film plating tool; and finally, testing the reflecting mirror after film coating. According to the invention, the boundary of the coating area is clear and has no shadow effect, and stray light crosstalk is reduced; and the film is good in film forming quality, small in film stress, excellent in optical performance, good in film firmness and high in space environment adaptability.

The invention relates to the technical field of optical fiber wireless communication and mobile forward transmission, in particular to a digital analog optical fiber wireless forward transmission transmitting end parameter self-adaptive optimization method and system based on reinforcement learning. Decomposing the normalized wireless signal into digital parts of all levels and a final analog residual error part through multi-level modulation, and transmitting the digital parts and the final analog residual error part in a time division multiplexing manner; a receiving end represents inter-symbol interference caused by link nonlinear distortion and bandwidth limitation, and the signal-to-noise ratio of a recovery signal is calculated based on the error vector amplitude. Parameters of a transmitting end are optimized and modeled into a Markov decision process, states comprise rounding factors, scaling factors, constellation forming factors and pre-equalization filter tap coefficients of all levels, and actions are discrete increments of the parameters; a reinforcement learning agent is constructed by using a dual deep action value network, and training is updated in combination with experience playback and a target network. The reward function comprises a threshold satisfaction item and a signal-to-noise ratio change item; parameters are interactively updated in the training stage, and online self-adaptive adjustment is performed in the reasoning stage.

The invention provides a photoresist composition and a preparation process thereof. The photoresist composition is prepared from the following raw materials in parts by weight: 80.0 to 100.0 parts of solvent, 20.0 to 40.0 parts of resin, 3.0 to 5.0 parts of photoinitiator, 1.0 to 3.0 parts of light stabilizer, 1.5 to 2.5 parts of tackifier, 1.0 to 1.5 parts of monomer, 1.0 to 2.0 parts of acid diffusion inhibitor and 0.5 to 2.0 parts of flatting agent. Wherein the acid diffusion inhibitor is prepared from perfluorocyclohexane, benzo-15-crown ether-5 and L-ethyl lactate, and the mass volume ratio g / mL of the perfluorocyclohexane to the benzo-15-crown ether-5 to the L-ethyl lactate is (2-3): (1-2): (1-2). According to the acid diffusion inhibitor disclosed by the invention, through the combined action of different mechanisms of the perfluorocyclohexane, the benzo-15-crown ether-5 and the L-ethyl lactate, the diffusion speed of acid is slowed down, so that the boundary between an exposure region and a non-exposure region is clearer, and the resolution ratio of photoresist is improved. By modifying the methacrylic resin, the surface energy and polarity of the methacrylic resin are changed, and the solubility of the resin after exposure is remarkably changed, so that the photoresist is easier to remove in a developing solution, and the definition and resolution of a pattern are improved.

The invention relates to the technical field of battery production, and discloses pole piece production equipment and a pole piece production process method, and the pole piece production equipment is suitable for processing a continuously moving current collector; the pole piece production equipment comprises a first coating head and a second coating head, wherein the first coating head is suitable for coating a current collector with first slurry; the first drying oven is arranged at the downstream of the first coating head and is suitable for drying the current collector coated with the first slurry; the second coating head is arranged at the downstream of the first drying oven and is suitable for coating the current collector with second slurry, and the second slurry is located on at least one side of the first slurry in the width direction of the current collector; and the second drying oven is arranged at the downstream of the second coating head and is suitable for drying the current collector coated with the first slurry and the second slurry. According to the pole piece production equipment provided by the invention, the conditions of permeation and material mixing on the edges of the ceramic slurry and the positive active material slurry when the ceramic slurry and the positive active material slurry are in a fluid state before drying can be avoided.

The application relates to a boundary attention guiding-based encoder-decoder medical image segmentation system and method, and belongs to the technical field of medical image processing.The application comprises an encoder, a decoder, a feature enhancement module and a boundary attention guiding module.Different scale features are obtained in the encoder by inputting a medical image, and the features are output to the decoder; the decoder completes medical image segmentation according to the features; the feature enhancement module is further connected after the output of the different scale features of the encoder, and is used for enhancing the semantic features of the encoder, combining semantic information of different receptive fields, and inputting the feature output of the encoder into the decoder again after the feature output of the encoder passes through the feature enhancement module; the boundary attention guiding module is arranged between adjacent decoder modules in the decoder, and is used for strengthening boundary information of the medical image.The application is excellent in generalization ability and robustness, and the obtained medical image segmentation result is clear in boundary and obvious in small target.

The present invention discloses a method for classifying hyperspectral remote sensing images using a hybrid convolutional neural network. The present invention comprises: 1. connecting 3D and 2D convolutional neural networks in series, adding parallel convolution blocks and non-local attention modules, and constructing a custom neural network; 2. dividing annotated hyperspectral images into a number of overlapping small data cubes as inputs of the model; 3. dividing samples into training sets and test sets according to a certain ratio; 4. inputting training set samples into the neural network in batches for training until the model is stable; 5. using the trained model to classify the hyperspectral image, evaluating the classification effect of the model through the pre-divided test set, and finally obtaining a classification result graph. The present invention makes full use of the rich spectral information and spatial information of the hyperspectral remote sensing image. At the same time, 1×1 convolution is used to compress the channel dimension of the feature map during the attention operation, thereby reducing the amount of calculation of the model and improving the training speed of the model.

This invention discloses a data processing method and system for government services, relating to the field of data transmission technology. The method includes: obtaining jitter-related USB events from USB events of a government self-service terminal; obtaining jitter-related government business events from government business events of the government self-service terminal based on the jitter-related USB events; obtaining a disturbance chain based on the jitter-related USB events and the jitter-related government business events, and determining the identifier of the disturbance chain; defining a target disturbance chain based on the identifier of the disturbance chain, and obtaining a disturbance chain pointing label; classifying all government data units according to the disturbance chain pointing label to obtain disturbance-related government data units and secure government data units. This invention improves the reliability and controllability of the government data processing process.

The present application relates to the technical field of stage lighting, and discloses an effect device for shaping stage light effect, comprising a lamp body, the lamp body comprising a connecting top seat and a lamp shell body, a light source is arranged in the lamp shell body, an adjusting device is connected to the lamp shell body, the adjusting device comprising: an extension shell body; two fixed pipes symmetrically connected to the extension shell body; an optical lens, both ends of the optical lens being connected to an upper cavity and a lower cavity respectively, the optical lens being a hollow structure, and the inner walls of the upper cavity and the lower cavity being fixedly connected to impellers; a connecting pipe, respectively connecting the upper cavity and the lower cavity; wherein, one side end face of the optical lens is a one-way perspective glass, the other side end face is ordinary glass, two fixed pipes are respectively connected to a liquid pipe, the two liquid pipes are both connected to an external water tank, a water pump is connected to the two liquid pipes, and the two liquid pipes are arranged on the inner wall of the lamp shell body, solving the problems of high energy consumption and single effect of the existing equipment.

The invention relates to the field of geophysics, and provides a magnetic anomaly inversion method, device, equipment and medium, and the method comprises the steps: obtaining magnetic anomaly observation data corresponding to an underground target region, and dividing an inversion region of the underground target region; calculating a smooth inversion result corresponding to the inversion region through a pre-constructed inversion expression based on the magnetic anomaly observation data, and calculating a sparse inversion result corresponding to the inversion region based on the smooth inversion result; updating the inversion model in the inversion expression based on the difference value between the sparse inversion result and the L0 norm of the preset smooth approximation function, and returning to the step of calculating the smooth inversion result and the sparse inversion result corresponding to the inversion region until the condition of stopping updating is reached; and predicting the magnetic body distribution of the to-be-observed area based on the updated inversion model. According to the scheme disclosed by the invention, accurate underground magnetic field intensity distribution and a clear boundary inversion result can be obtained, and the stability and the accuracy of a magnetic anomaly inversion result are improved.

The utility model discloses a Mark point structure, which adopts at least two rectangular parts which are arranged in a crossed manner to form a bonding pad area, and compared with a traditional circular structure, the composite geometric shape of the bonding pad area can provide higher feature vector dimension in a machine vision system, the HOG feature value is improved by at least 30%, the algorithm identification accuracy is greatly improved, and the reliability of the structure is improved. Especially in a high-density BGA packaging area, the positioning precision of the center coordinates of the cross points can reach + / -0.01 mm, the identification degree of the Mark points on the PCB is greatly improved, and the problem that the Mark points are difficult to distinguish due to the low identification degree is effectively solved.

This invention discloses a multifunctional energy-saving block forming device and method, relating to the field of block forming technology. The invention includes a conveyor line with a base plate at its top and a frame mounted above it. Inside the frame is a lifting and lowering pressing head, with several inner pressing blocks fixedly installed at its bottom. Lifting and lowering outer pressing blocks are located on both sides of each inner pressing block. This invention, through the novel design of inner and outer pressing blocks, creates a trapezoidal sawtooth pattern on the joint surface of the composite brick. Compared to a flat interface that relies entirely on chemical bonding, the trapezoidal sawtooth structure forms a regular tenon-and-mortise interlocking mechanism at the interface, resulting in clear boundaries, reduced separation, and high composite pressing strength. The alternating lifting and lowering design of the inner and outer pressing blocks, combined with the longitudinal conveying and transverse spreading of the material frame, ensures five-sided isolation after the outer layer is pressed, minimizing interlayer mixing and maintaining clear boundaries.

The invention relates to an optical target based on a three-dimensional cavity type structure. The optical target comprises a black box body and a white plate, a round hole is formed in one side surface of the black box body, and a light absorption cavity is formed in the box body; the white plate is connected with the black box body and arranged in the round hole, and an annular area communicated with the light absorption cavity is formed between the white plate and the black box body. When light irradiates the optical target, one part of the light is reflected by the white plate, and the other part of the light enters the annular area around the white plate and then enters the light absorption cavity, and the light is gradually attenuated after being reflected for multiple times in the cavity, so that an extremely low gray value close to a theoretical black body is formed in the annular area; the boundary between the light spot formed on the white plate and the annular area is distinct, and a good gray difference is formed between the light spot and the annular area.

The invention relates to an SCA radio station system based on a smart deployment module and an upgrading method, the radio station system comprises an upper computer, an ARM chip, a radio frequency chip, an FPGA chip and the smart deployment module, the smart deployment module is separable from the SCA radio station system, and the smart deployment module comprises a universal driver, a special driver, an SCA operating system component, an SCA waveform and a management system. The upper computer is provided with main control software, the ARM chip is provided with embedded software, and the FPGA chip is provided with FPGA software. Compared with the prior art, the system has a flexible access mode compared with a traditional system, has a clear boundary with the traditional system, does not affect the traditional system when the software system is upgraded and transformed, and has flexible and diversified function expansion capability.

This invention discloses a virtual immunohistochemical staining method and system based on relation generative adversarial networks (GANs) and sequence slide data, comprising the following steps: Step S1, constructing a sequence slide dataset, wherein each H&E-stained slide is followed by three consecutive Ki67-stained slides; Step S2, constructing a relation generative adversarial network (GAN) model, the model comprising two ResNet generators and two relation discriminators, used to train and evaluate the credibility of the sequence relationship between image pairs; Step S3, performing two-stage training on the relation generative adversarial network model, namely, basic style pre-training and Z-axis alignment relation adaptation. This invention fundamentally solves the Z-axis alignment problem, resulting in higher image fidelity and pathological accuracy, significantly improving clinical application value, and providing new research resources and evaluation paradigms.

The present invention discloses an intelligent image detection method for oral orthodontic treatment, which relates to the technical field of oral orthodontic image detection. It is implemented by a data acquisition module, a data processing module, an image processing module and a result output application module, and the pre-processed image data is converted into a gray space, and the image processing module is used to process the image data. The present invention has the introduction and weighted calculation based on the three channels of red, green and blue, as well as the analysis and comprehensive calculation of gray values, original color images and contrast, so as to retain part of the color information and reduce information loss, improve the contrast and clarity of the gray image, make the boundaries of teeth and periodontal tissues clearer, and realize more accurate and comprehensive and reliable orthodontic effect evaluation. In addition, the adjacent submodules of the present method are associated and the overall algorithm system has the characteristics of cyclic drop, so that the practicality of the present method is better and the adaptability is stronger.

This invention discloses a method for preserving cherry blossom germplasm, belonging to the field of forestry breeding technology. The method includes: (1) cultivating rootstocks with 6-10 primary branches, each primary branch containing 3-4 secondary branches; (2) selectively pruning secondary branches before grafting, retaining 1-2 weak outer branches as nutrient branches; (3) grafting in batches, first grafting strong inner branches, and then grafting reserved nutrient branches after survival; (4) determining the number of scions according to the branch diameter gradient; (5) supporting field management measures. This invention, through the core technology combination of "graded branching + batch grafting + retention of nutrient branches", can preserve 6-10 germplasm from a single rootstock, with a germplasm preservation rate of over 95%, increasing land utilization by 7 times, and reducing rootstock cost by 87.5%. It solves the technical problems of traditional cherry blossom germplasm preservation, such as large land occupation, high cost, and unstable survival rate, and is particularly suitable for the construction of large-scale cherry blossom germplasm resource banks.

The invention discloses a tumor ablation image fusion modeling method based on deep learning, and relates to the technical field of intelligent medicine, and the method comprises the steps: obtaining a plurality of preoperative tumor images of a tumor patient before an ablation treatment puncture operation is carried out on a tumor; performing image fusion on the first ultrasonic tumor image, the first CT tumor image and the first MRI tumor image to obtain a preoperative fusion tumor image; the method comprises the following steps of: acquiring a plurality of intraoperative tumor images of a tumor patient in the process of performing ablation therapy puncture operation on the tumor; obtaining an intraoperative fusion tumor image for the second ultrasonic tumor image, the second CT tumor image and the second MR I tumor image; and according to the extracted spatial mode data and deep learning training data, constructing a deep learning model, and carrying out training optimization on the constructed deep learning model to obtain a tumor ablation image fusion model. According to the invention, the treatment effect of the ablation treatment puncture operation can be accurately evaluated based on the tumor ablation image.

According to a method for producing a three-dimensional shaped food, the method comprising a step of turning a curdlan dispersion liquid into a heat irreversible gel, and a step of ejecting and laminating the gel, it is possible to obtain a three-dimensional shaped food that may withstand precise shaping with good handling properties at the time of ejection but with high shape retention during and after lamination and also has heat resistance after forming.