  Deep learning has dramatically improved the performance in many application
areas such as image classification, object detection, speech recognition, drug
discovery and etc since 2012. Where deep learning algorithms promise to
discover the intricate hidden information inside the data by leveraging the
large dataset, advanced model and computing power. Although deep learning
techniques show medical expert level performance in a lot of medical
applications, but some of the applications are still not explored or under
explored due to the variation of the species. In this work, we studied the
bright field based cell level Cryptosporidium and Giardia detection in the
drink water with deep learning. Our experimental demonstrates that the new
developed deep learning-based algorithm surpassed the handcrafted SVM based
algorithm with above 97 percentage in accuracy and 700+fps in speed on embedded
Jetson TX2 platform. Our research will lead to real-time and high accuracy
label-free cell level Cryptosporidium and Giardia detection system in the
future.
