Hyperspectral Imaging for Biological Stains Detection-Reference-Cited by-同舟云学术

Hyperspectral Imaging for Biological Stains Detection

Published:2022-10-26 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)
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Author:

Melappioni Leonardo¹,Giulietti Nicola²,Discepolo Silvia¹,Martarelli Milena¹,Castellini Paolo¹

Affiliation:

1. Department of Industrial Engineering and Mathematical Sciences,Ancona,Italy

2. Politecnico di Milano,Department of Mechanical Engineering,Milan,Italy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9967443/9967445/09967666.pdf?arnumber=9967666

Reference22 articles.

1. A Neural Network based Digital Forensics Classification

2. Machine Learning Forensics: A New Branch Of Digital Forensics;rughani;International Journal of Advanced Research in Computer Science,2017

3. Enabling Trust in Deep Learning Models: A Digital Forensics Case Study;aditya;17th IEEE International Conference on Trust Security and Privacy in Computing and Communications (TrustCom),2018

4. Sigmaz random forest, classification and confidence;fornaser;Measurement Science and Technology,2019

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1. Measurement technique based on hyperspectral imaging for occulted blood stain detection;2023 IEEE International Workshop on Technologies for Defense and Security (TechDefense);2023-11-20

2. A Novel, Multimodal, High Throughput Screening Microscope Platform for Automating the Analysis a of Vast Populations of Forensics Traces;2023 IEEE International Workshop on Technologies for Defense and Security (TechDefense);2023-11-20

3. Neural network based hyperspectral imaging for substrate independent bloodstain age estimation;Forensic Science International;2023-08