Multimodal Sensor Fusion with Deep Learning

Abstract

This report documents the efforts over the three year 6.1 base program titled Multimodal Sensor Fusion with Deep Learning. Herein a novel framework for fusing hyperspectral imagery (HSI) and LiDAR data for urban land use and land cover classification is detailed. In this approach multimodal sensor fusion was enhanced by utilizing deep learning and fuzzy logic to amalgamate information between spatial and spectral domains. Deep learning techniques enabled exploitation of mid and high level correlations between contrasting domains that have weak correlation between low level representations. The introduction of fuzzy logic further improved sensor fusion by providing advantages with difficult samples and the opportunity to gain network explainability.

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Document Details

Document Type
Technical Report
Publication Date
Nov 20, 2020
Accession Number
AD1115817

Entities

People

  • Elizabeth A. Gilmour
  • Kristen L. Nock
  • Samuel N. Blisard

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Intelligence Software
  • Computer Vision
  • Data Fusion
  • Deep Learning
  • Detection
  • Detectors
  • Dimensionality Reduction
  • Fuzzy Logic
  • Information Processing
  • Information Science
  • Information Systems
  • Machine Learning
  • Military Research
  • Mobile Phones
  • Neural Networks
  • Recognition
  • Remote Sensing
  • Sensor Fusion
  • Teamwork

Readers

  • Neural Network Machine Learning.
  • Sensor Fusion and Tracking Systems.
  • Technical Research and Report Writing.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks