@BactLAB
@BactLAB Summary
@BactLAB is a free Android app in Productivity by Shimadzu Diagnostics Corporation. Released in Oct 2023 (3 years ago). It has about 4.1K+ installs Based on AppGoblin estimates, it reaches roughly 228 monthly active users . Store last updated Aug 4, 2026
Recent activity: 46 installs this week (165 over 4 weeks) showing strong growth View trends →
@BactLAB SDKs Summary
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App Description
Colony Counter Global Service with AI-deep learning
The safety and security of foods are important for humans to live. The examination of bacteria in foods and drinking water can be easily available to everyone. The product supports human life in any place and region. Making it easy bacterial counting, by using a familiar mobile device for everyone around the world, trying to promote operational efficiency using the global cloud and AI, adding value to CompactDryâ„¢ to play a role in the improvement of the QOL, keeping these ideas in mind we have developed the application for everyone engaging on health and safety of food.
　You can easily determine the bacterial (colony) count cultured in CompactDry™ using your smartphone.
â– Targeted Products ( 7 Types )
CompactDryâ„¢ TC ( General Bacteria )
CompactDryâ„¢ TCR ( General Bacteria )
CompactDryâ„¢ EC ( E.coli / Coliforms )
CompactDryâ„¢ CF ( Coliforms )
CompactDryâ„¢ YM ( Yeast / Fungus )
CompactDryâ„¢ YMR ( Yeast / Fungus )
CompactDryâ„¢ ECO ( E.coli )
â– Primary Functions
Colony counter [ PC / Android / iOS ]
- Colony count arbitrary adjustment function equipped
- Cloud storage function for count data
Count report [ email ]
Uniform management of data by company (*Optional)
â– Remarks
- Regarding the colony counting process, the processing with the initial AI model released in August 2018 had implemented counting technology image processing that combines "image processing" and "machine learning (Deep Learning)" for colony position detection. In the AI model released in July 2023, object detection AI network (machine learning model) [YOLOv4] that processes position (area) detection and class classification in one network is used as a backbone and implemented as a hard-tuning AI enabling business use by repeated inference verification tests specializing in colony detection (counting) .
- The cloud image recognition technology used in this service employs artificial intelligence (AI) technology for image recognition system jointly developed by Shimadzu Diagnostics Corporation and Hitachi Solutions, Ltd.
- Restrictions for input images in Colony Counter No warranty of accuracy is given for the following images.
1. Image resolution of less than 800 pix x 1200 pix.
2. The background color is not white.
3. Colored medium.
4. A viscous sample is added.
5. Food residues are contained.
6. Highly concentrated colonies.
Other
・The count result of "0" does not mean a negative result.
・Detection range is between 1–250 cfu/plate.
・There are two types of misreads that can occur when using the @BactLAB™.
- @BactLABâ„¢ Application did not detect all of the colonies specific to the CompactDryâ„¢ plate.
- The counter detected all the colonies but it categorized them incorrectly.
- Please note that the specification or performance may be changed without notice.
- The cloud image recognition technology utilized in this service employs the artificial intelligence (AI) technology for image recognition system jointly developed by Shimadzu Diagnostics Corporation and Hitachi Solutions, Ltd.
- Please see here.
https://corp.sdc.shimadzu.co.jp/english/products/global/bactlab/