Adaptive Cell Classifier for Remote E-Lab Experiments Based on Adaptive Neuro-Fuzzy Inference System

Practical experimentation and observations play an essential role in the experience of learning. And several emerging remote-labs are making the best use of the internet to achieve a better experience for the students through providing several real experiments from a website. The field of biotechnology involves several experiments that involves living cells manipulation for analysis and understanding. In this study, an adaptive living cell classifier is proposed through the remote e-lab technology. The classifier is able to distinguish between several types of cells. Furthermore, the classifier continuously learns through utilizing each new input image to train and improve its adaptive-neuro fuzzy (ANFIS) classifier for better decisions in the future. The results achieved from the proposed system are promising and opens the door for further experiments implementation along this field.

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