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AlgaeC plankton counting and analysis intelligent identification system (algae identification module)
AlgaeC plankton counting and analysis intelligent identification system (algae identification module) I. Main performance indicators: 1) Microscopic i
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AlgaeC plankton counting and analysis intelligent identification system (algae identification module)
1、 Main performance indicators:
1) Microscopic imaging: It can manually control the observation, shooting, storage, and continuous automatic shooting of up to 200 images at equal intervals.★ It has real-time preview saturation warning and automatic background correction features.
2)Algae expert library displayed in both Chinese and Latin languagesThere are a total of 15 phyla, 1647 genera, and 14831 species in the algae database, with over 183756 valid algae images. The genera and contents of each database can be expanded independently.
3)Intelligent identification of algae:It has the intelligent feature of automatically comparing algae images based on similarity in image shape, color, texture, etc.And through morphological search, fuzzy keyword search, common algae search, and taxonomic search, algae can be quickly identified through image and text comparison.Automatically index the user count table of algae into a small database of the watershed, making it faster to search for images.
4)Algae counting and morphological measurement function: a. Plankton classification labeling: Different colors and sizes of color circles are used to label various plankton, and various plankton in 200 captured images are automatically counted by category by clicking and accumulating (different magnification counting results and multiple sample counting results can be merged); b、 Automatic sorting of dominant species, sorting by phylum (class), and percentage analysis of dominant community composition;c、 Automatically calculate Shannon Wiener index, uniformity index, algae density conversion, and planktonic animal abundance conversion; d、 Assist in calculating the biomass of plankton using a large number of shape models (with 34 built-in geometric models, individual/cell volume can be calculated by measuring a small number of parameters).Built in counting tables for common freshwater algae, common marine algae, etc., and can be edited, exported, and imported by oneself. It can be measured by field of view area, algae population area, individual area of planktonic animals, cell diameter, algal filaments, flagella length, body length and antennae of planktonic animals, as well as branch angle and branching angle.
5)The Microcystis Analysis Module can automatically learn and analyze the cell count of clustered Microcystis populations, and can automatically count granular or single-cell microalgaeChain microalgae cellsPlanktonic animals such as nematodes.
6)★ Super depth of field extended multi focus fusion 3D high-definition imaging. The automatic stitching, cropping, editing, and correction features of multi view images. The color and shape of algae have automatic learning and classification characteristics, which can monitor and correct the conversion of algae categories, and perform secondary learning and preservation of classification features.
7)It has the automatic image extraction feature of planktonic cells, which can quickly extract their main edge feature images.Has the ability to clarify blurry and overlapping images of planktonic organisms.
8)The analysis software has the feature of online autonomous upgrade.

2、 Configuration:
1) Professional level20 million pixel color CMOS camera (Sony 1 "large chip)Three eye microscope standard C interface
2) 1 set of intelligent identification system software for plankton counting analysis (algae identification module)
3) 1 branded computer (Core i5 9th generation or above CPU/8GB memory/1TB hard drive/21 'color display/wireless network card, used under the full professional version Windows 10 operating system)

Note: In this technical proposal★ Payment must be responded toOtherwise, it is a significant deviation.
Three eye microscope needs to be equipped separately.Suggestion: For research level Olympus BX53 and above:
Olympus BX53T-32P01 research grade three eye biological microscope (including BX53F frame, three eye observation tube, D-type 6-hole objective turntable, BX3 mirror arm, flat field achromatic objective lens (100XO, 40X, 20X, 10X, 4X), 10 times wide field adjustable eyepiece). If there is sufficient funding, it is recommended to add a 40X DIC phase difference objective lens for effective imaging of transparent bodies.
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