FGRC-Net: A high-information interactive convolutional neural network for identifying ink spectral information

Author:

Shi YanORCID,Zhang Qinglun,Kang Siyuan,Yin Chongbo,Liu Xiaotong,He Xinyu

Funder

Natural Science Foundation of Jilin Province

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference41 articles.

1. Visual inspection of fault type and zone prediction in electrical grids using interpretable spectrogram-based CNN modeling;Ardito;Expert Systems with Applications,2022

2. Raman spectroscopy for forensic analysis of inks in questioned documents;Braz;Forensic Science International,2013

3. COVID-19 detection on Chest X-ray images: A comparison of CNN architectures and ensembles;Breve;Expert Systems with Applications,2022

4. Devassy, B. M. & George, S. (2019, November). Ink Classification Using Convolutional Neural Network, Norwegian Information Security Conference, Norway, NO.

5. Automatic neural network hyperparameter optimization for extrapolation: Lessons learned from visible and near-infrared spectroscopy of mango fruit;Dirks;Chemometrics and Intelligent Laboratory Systems,2022

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