6 results about "Microphotograph" patented technology

The invention relates to the cross technical field of artificial intelligence and mineralogy, and discloses an AI mineral automatic identification method based on an optical microphotograph, comprising the following steps: step S1: data acquisition and preprocessing; s2, data classification and labeling: constructing a rock microscopic image data set by adopting a two-stage labeling process; s3, building and training a deep learning model; s4, model optimization and quantitative feature learning; s5, developing a software platform; and S6, hardware system combination and full-process automation are carried out. In the aspect of operation convenience, a full-automatic slice scanning hardware system is constructed and combined with an intelligent software platform, so that full-process automatic operation from automatic rock slice scanning, automatic mineral analysis to automatic PDF report generation is realized, manual intervention is greatly reduced, the operation difficulty and complexity are reduced, and the working efficiency is improved. And even an operator without rich experience can easily complete complex mineral identification work.

The present application provides a method, device and computer-readable medium for performing segmentation processing on an image. The method according to the present application includes: obtaining a target image to be processed, the target image containing multiple target objects; performing segmentation processing on each target object contained in the target image by using a target segmentation model and a target clustering algorithm; and generating segmentation result information of the target image. The present application performs image segmentation processing on objects with overlapping slender structures in an image by combining a segmentation model and a clustering algorithm, and achieves excellent image segmentation effects; and according to the method of an embodiment of the present application, by combining a segmentation model and a clustering algorithm, image segmentation processing is performed on sperm micrographs in a sperm detection scenario, and the overlapping sperm tails are accurately identified and segmented. The entire process does not require human intervention, and automatic sperm segmentation is achieved, which greatly improves the efficiency of sperm segmentation in micrographs.

The present invention discloses a method for identifying water chestnut lodging resistance in the field of water chestnut lodging resistance identification technology, comprising the steps of: selecting 10 water chestnut varieties for identification; trimming, dehydrating, embedding, slicing, staining, and sealing the selected samples to make paraffin sections; observing the prepared paraffin sections with a microscope and photographing them; a fourth step of observing the microphotographs taken after amplification by any multiple using software, and scanning and browsing the software to select the target area of ​​the tissue for 200 times imaging; a fifth step of measuring the anatomical structure index of each slice of water chestnut leaf tissue using analysis software in a unified manner with millimeters as the standard unit after imaging; and a sixth step of drawing and analyzing the data obtained from the experiment. This method provides making water chestnut into paraffin sections and observing their different indicators under a microscope, so that the lodging resistance of water chestnut can be identified.

Method for measuring the crystalline misorientation of a single-crystal blade. Method for measuring the crystalline misorientation of a single-crystal blade (10) comprising a material formed of dendrites (30) having a main trunk (32) extending in a principal direction (Z') and branches (34), the method comprising defining a reference frame (XYZ) of the blade comprising a radial direction (Z), mechanical and chemical treatment of the blade (10) in a baseline (P1) to acquire a first image (I1) by microscopy, mechanical and chemical treatment of the blade (10) in a comparison plane (P2) radially offset from the baseline (P1) by a distance (D), to acquire a second image (I2) by microscopy, processing the first and second images (I1, I2) so as to compare the position of the main trunk (32) of each dendrite (30) between the two images (I1,I2) and thus deduce the orientation of the principal direction (Z') of the dendrites (30) with respect to the radial direction (Z). Figure for the abbreviation: Fig. 4.

The invention relates to a method and a device for preparing a grinding pattern for a metallurgical sample (1), wherein, after preparing the sample (1), a thermal contrasting of the surface is carried out by laser equipment, wherein, using a UKP laser (2), at least the following processing steps are carried out: cleaning (R) the surface of the sample (1) with an ablation depth between 1 and 50 µm to reveal joining gap structures (300); contrasting (K) the cleaned surface of the sample (1) with an ablation depth between 0.5 and 20 µm to make joining structures (400) visible; laser etching (A) the contrasted surface of the sample (1) via the ablation-free creation of a thermal annealing colour structure (500) and / or surface oxidation.

A computer-implemented method, when executed on data processing hardware, causes the data processing hardware to perform operations. The operations include i) via application of a machine learning algorithm to a micrograph representative of a metallic material, detecting clusters of dendrite arms in the metallic material and generating an image frame based on the micrograph and representative of the clusters of dendrite arms, ii) detecting, via application of a watershed algorithm to the image frame, individual dendrite arms within the clusters of dendrite arms, iii) applying at least one filter to the image frame, iv) identifying at least one cluster of dendrite arms in the image frame that satisfies the at least one filter, and v) generating, for the at least one cluster of dendrite arms, a cluster profile including at least an average dendrite arm spacing (DAS) value for the at least one cluster of dendrite arms.