6 results about "Morphological transformation" patented technology

The invention provides an AI-based multi-terminal-oriented real-time editable data visualization system and method, and the method comprises the steps: building a visual canvas with a dimension field of a business data set in a business data source as a longitudinal axis and a measurement field of the business data set in the business data source as a horizontal axis, and initializing an AI data view of the business data source; recombining the display layout of the AI data view on each display terminal on the basis of the size characteristics of the canvas container in each display terminal, triggering the morphological transformation logic of the editing component to present the matched editing component on each display terminal, receiving the editing operation of a user on the editing component on each display terminal, and displaying the edited editing component on each display terminal. And performing derivative updating on the view state in each display terminal based on the data binding relationship and the layout dependency relationship among the editing components, and the operation type and the semantic context of the editing operation. Based on the scheme, automatic generation and intelligent linkage updating of the multi-end view based on the AI and the responsive rule can be realized.

The application discloses a wild animal video target detection method based on a feature fusion network, and comprises the following steps: collecting and labeling wild animal image and video data; performing morphological transformation, color transformation and contour destruction preprocessing; sequentially inputting the preprocessed image and video data into a feature extraction network to obtain multi-scale features; performing feature fusion on the extracted multi-scale features, fusing multi-scale features and same-scale features of adjacent image frames for the video data, and only fusing multi-scale features for the image data, finally obtaining multi-scale fusion features; inputting the multi-scale fusion features into a feature prediction network to obtain a prediction result; comparing the prediction result with a label in the training stage, calculating a loss function, performing gradient back propagation, completing model parameter updating, and until the network converges; in the inference stage, the prediction result is post-processed to obtain the final output result.

The paper medical record digitization information extraction method, system, equipment and medium based on image edge detection and Res-CRNN, the method comprises: sequentially performing gray processing, edge sharpening processing, image line recognition and rotation correction, mask processing and projection transformation on the original image with color information, generating handwritten digital training data through morphological transformation, and performing character recognition on the processed image based on the generated handwritten digital training data and Res-CRNN deep learning model to obtain the final text digital recognition result; the system, equipment and medium are used for realizing the paper medical record digitization information extraction method based on image edge detection and Res-CRNN; the original image is processed through gray processing, edge sharpening processing, image line recognition and rotation correction, and the digitization information extraction of the medical record image is realized through Res-CRNN, so that the paper medical record digitization information extraction method has the characteristics of efficient and accurate extraction of case image information and simple operation steps.

The invention relates to the technical field of information identification, in particular to a medicine information identification method and system based on AI vision, and the method comprises the following steps: importing a medicine outer package image, adjusting the contrast and brightness of the image, removing background noise, and obtaining a processed image. According to the method, the image of the external package of the medicine is processed, so that the definition of the image is improved, and high-quality input is provided for feature extraction. And after conversion to the gray mode, through analysis and morphological transformation of the convolutional neural network, accurate capture of drug shapes and textures is improved, and more accurate drug category classification is realized. According to the method, the accuracy of medicine identification is effectively improved, particularly the diversity and complexity of medicine processing are excellent, the error rate in medicine distribution is reduced, the problems of wrong distribution, missed distribution and frequent distribution in the medicine distribution process are reduced, and the medicine circulation efficiency is optimized.

The application discloses a signal fluctuation extraction method combining a Hadamard matrix and mathematical morphology, and comprises the following steps: determining the order m of the Hadamard matrix and the specific number l of rows to be selected according to signal characteristics and sampling accuracy; taking the lth row of the selected Hadamard matrix as a structure element g to perform mathematical morphology operation on an input signal f to obtain a signal fluctuation part and complete the extraction operation. According to the application, a certain row in the Hadamard matrix is selected as the structure element according to signal characteristics, and the order of the matrix is determined; the characteristics that the Hadamard matrix only takes values of 1 and -1 are utilized; the fundamental component in the signal is suppressed through the morphological operation; and the fluctuation part is extracted. The orthogonality of the Hadamard matrix is fully utilized, the Hadamard matrix is used as the structure element for the morphological transformation, the signal can be processed simply and quickly, and the characteristic information is extracted. The application of the mathematical morphology can accurately analyze the signal in the time domain.

The present invention relates to an equipment for cleaning and morphological transformation of wastes so that same are manageable, comprising at least one reactor (1) made up of several modules (2a, 2b, 2c, 2d) that can be disassembled and coupled together, each of which internally incorporates means to carry out a specific function that, at least, covers the function of loading, cleaning and morphological transformation of process wastes, discharge and dehydration, and control and electrical power. Preferably, the modules are four modules consisting of: a loading module (2a), a module that contains the process reactor body (2b), a discharge (2c) and dehydration module, and a control (2d) and power module and same are removable, are manufactured with measurements and exterior design meeting the ISO 20 and ISO 40 requirements stipulated for maritime containers or the like.