AlgaEye

Work for higher water quality

ABOUT

Safe water quality relies on a proper algae management. As algae conditions will also affect the smell and taste of water, to have a comprehensive understanding of algae growth should be one of the major operations for water management. Anavision AI model, AlgaEye, learns from expert-annotated algae to recognize 28 algae features as well as identify algae type from similar morphology to help professionals efficiently manage a safe water quality. The involvement of AI helps experts to automate the process of detecting harmful algae in water samples and regulate algae growth under control. AlgaEye will offer improvements in efficiency, accuracy, and result scalability by its automatic detection of work. It will also provide consistent and accurate results for experts future analysis. The output includes labelled images, statistics result, and summary report.

WHY

Customized

Given the diversity of algae species,
specific recognition algorithms are designed
for each species according to your needs

Efficient

Simple operation method contributes to
quick result output with simultaneous identification of 28 algae species

Automated

Web-based interface will address your
microscopic images automatically

Accurate

Specific recognition algorithms are designed for each algae species.
Sophisticated annotations take algae's irregular shape into account
by tracing its boundary for higher accurate output

WHAT OFFER

Algae Cell Counting

AlgaEye helps to identify 28 types of algae species simultaneously based on the microscope images. Accuracy improves when “Retrain” exercise is being done properly, instead of extensive manual work. Difficulty of algae sample collection due to the high diversity will be resolved by our image augmentation technique.

Imagery Detection Output

With a clear detection on every algae boundary, AlgaEye can clearly segment every respective algae even when they are overlapped. Detected algae is highlighted with different colors and marked with corresponding algae types and confidence levels in respective positions.

User Interface

A web-based algae detection system provides Drag and Drop feature for file import. Drag the microscopic images and system will identify 20 types of algae simultaneously.