Ground-Based Hyperspectral Image Surveillance System for Explosive Detection: Methods, Experiments, and Comparisons-Reference-Cited by-同舟云学术

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Ground-Based Hyperspectral Image Surveillance System for Explosive Detection: Methods, Experiments, and Comparisons

Published:2023 Issue: Volume:16 Page:8747-8763
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Kütük Mustafa¹^ORCID,Geneci İzlen¹^ORCID,Bilge Özdemir Okan¹^ORCID,Koz Alper¹^ORCID,Esentürk Okan²^ORCID,Yardımcı Çetin Yasemin³^ORCID,Alatan A. Aydın⁴^ORCID

Affiliation:

1. Center for Image Analysis, Middle East Technical University, Ankara, Turkey

2. Department of Chemistry, Middle East Technical University, Ankara, Turkey

3. Informatics Institute, Middle East Technical University, Ankara, Turkey

4. Center for Image Analysis and Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey

Funder

Havelsan Teknoloji Radar San. ve Tic. Inc., Turkey

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/9973430/10197158.pdf?arnumber=10197158

Reference62 articles.

1. Standoff hyperspectral imaging of explosives residues using broadly tunable external cavity quantum cascade laser illumination

2. UIU-Net: U-Net in U-Net for Infrared Small Object Detection

3. Differential spectroscopic imaging of particulate explosives residue

4. More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification

5. Long-Wave Infrared (LWIR) Molecular Laser-Induced Breakdown Spectroscopy (LIBS) Emissions of Thin Solid Explosive Powder Films Deposited on Aluminum Substrates

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2. Pyramid Cascaded Convolutional Neural Network with Graph Convolution for Hyperspectral Image Classification;Remote Sensing;2024-08-11

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