Information-driven Guidance and Control of Heterogenous Underwater Sensor Networks for Adaptive Target Detection and Classification
Project Description:
Project Description:
This project develops information-driven navigation and control algorithms for underwater target detection and identification based on the Convolutional Neural Networks (CNN).
Peer-Reviewed Publications:
Peer-Reviewed Publications:
- Pingping Zhu, Jason Isaacs, Bo Fu, Silvia Ferrari, “Deep Learning Feature Extraction for Target Recognition and Classification in Underwater Sonar Images,” IEEE Conference on Decision and Control (CDC), 2017. [Link]
- Shi Chang, Jason Isaacs, Bo Fu, Jaejeong Shin, Pingping Zhu, and Silvia Ferrari, “Confidence Level Estimation in Multi-target Classification Problems,” SPIE Defense + Commercial Sensing, 2018. [Link][PDF]