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Automatic colony counter
new product
Product Description
ICON automatic colony counter, unique AI intelligent algorithm counting, independent learning is not easy to identify the colony morphology, improve the colony library, counting and identification accuracy of up to 98%, extremely easy to operate the interface, so that the user can simply click the button to complete the colony counting.
Minimalist operation settings
Extremely simplified software setup interface, no need to manually set mechanical switches and complicated preselection parameters, one key analysis, the fastest 3 seconds counting
Original AI Intelligent Algorithm
AI algorithm actively learns and trains unfamiliar morphology colonies, faster and more accurate colony counting, counting accuracy >98%.
Full Automation Expansion
Open Application Programming Interface (API) for any connection to an external robot
Product Specification
Computing system: embedded computing system, computing core is built into the host to avoid damage caused by computer viruses and other abnormal factors.
Software system: manual correction to support regional selection, regional anti-selection, single addition, single deletion, support pre-selection of multiple regions at the same time counting analysis
Counting type: support spiral coating method, pouring method, paper sheet method, membrane filtering method, contact disk counting, glove embossing counting, etc.
Colony identification: ability to distinguish impurities, air bubbles, adherent colonies, heterogeneous colonies and overlapping colonies.
Sample size: 60mm/90mm/120mm/150mm standard round petri dish, system automatic identification
Lamp source: Built-in top light source, bottom light source, no mechanical switch control, automatic dimming, 254nm UV lamp for sample compartment disinfection (optional), 366nm UV lamp for fluorescence colony counting (optional)
Sample compartment: fully concealed sample compartment with motorized door
Data transmission: Gigabit Ethernet cable or WIFI wireless data transmission
Product Features
Autonomous learning does not easily recognize colony morphology and improves colony libraries