Efficient, Robust and Explainable Situational Assessment and Awareness AI-ML System Using Multi-Modal Sensing and Deep Learning Approaches

Abstract

In this project, we will make systematic efforts to achieve situational assessment and awareness (SAAW), which is of central importance to military operations in today s warfare and humanitarian assistance and disaster response (HADR) applications. We will emphasize on three aspects in our work on the fundamental researches in Artificial Intelligence and Machine Learning (AI-ML) methods- 1) data and computing efficient so that the system can perform well with small data size and readily available computers, which are the norm in most edge-AI military and HADR missions; 2) robust against noisy data, human errors, and intentional adversarial attacks when the AI-ML system is deployed; and 3) explainable- our models and systems will provide means to justify and certify the decisions with various techniques so that they are not black boxes but transparent, interpretable, justifiable and certifiable ones.

Document Details

Document Type
DoD Grant Award
Publication Date
Mar 14, 2024
Source ID
FA95502320002

Entities

People

  • Jie Wei

Organizations

  • Air Force Office of Scientific Research
  • Research Foundation of The City University of New York
  • United States Air Force

Tags

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks