Documents Counterfeit Detection Through a Deep Learning Approach
暂无分享,去创建一个
[1] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[2] Allah Bux Sargano,et al. Android-Based Verification System for Banknotes , 2017, J. Imaging.
[3] Min-Jen Tsai,et al. Deep learning for printed document source identification , 2019, Signal Process. Image Commun..
[4] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Mickaël Coustaty,et al. Local Binary Patterns for Document Forgery Detection , 2017, 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR).
[6] John W Bond,et al. Identification of forged Bank of England £20 banknotes using IR spectroscopy. , 2014, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.
[7] Mohamed Deriche,et al. A bibliography of pixel-based blind image forgery detection techniques , 2015, Signal Process. Image Commun..
[8] Abhishek Das,et al. Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[9] Oriol Ramos Terrades,et al. Evaluation of Texture Descriptors for Validation of Counterfeit Documents , 2017, 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR).
[10] Vladlen Koltun,et al. Multi-Scale Context Aggregation by Dilated Convolutions , 2015, ICLR.
[11] Jian Sun,et al. Identity Mappings in Deep Residual Networks , 2016, ECCV.
[12] Faisal Shafait,et al. Printer Identification Using Supervised Learning for Document Forgery Detection , 2014, 2014 11th IAPR International Workshop on Document Analysis Systems.
[13] Oriol Ramos Terrades,et al. Recurrent Comparator with Attention Models to Detect Counterfeit Documents , 2019, ICDAR.
[14] Volker Lohweg,et al. Banknote authentication with mobile devices , 2013, Electronic Imaging.
[15] Luc Patiny,et al. Development of a systematic computer vision-based method to analyse and compare images of false identity documents for forensic intelligence purposes-Part I: Acquisition, calibration and validation issues. , 2016, Forensic science international.
[16] Josep Lladós,et al. Banknote Counterfeit Detection through Background Texture Printing Analysis , 2016, 2016 12th IAPR Workshop on Document Analysis Systems (DAS).
[17] Antoine Doucet,et al. Find it! Fraud Detection Contest Report , 2018, 2018 24th International Conference on Pattern Recognition (ICPR).
[18] Rob Fergus,et al. Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[19] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[20] Chulhee Lee,et al. Detection of counterfeit banknotes using multispectral images , 2018, Digit. Signal Process..
[21] Carlos Roberto Appoloni,et al. Characterization of Brazilian banknotes using portable X-ray fluorescence and Raman spectroscopy. , 2019, Forensic science international.
[22] Ching Yee Suen,et al. Modified HOG Descriptor-Based Banknote Recognition System , 2018 .
[23] Claude Roux,et al. Image processing of false identity documents for forensic intelligence. , 2016, Forensic science international.
[24] Thomas M. Breuel,et al. Using DCT Features for Printing Technique and Copy Detection , 2009, IFIP Int. Conf. Digital Forensics.
[25] Wolfram Burgard,et al. Self-Supervised Model Adaptation for Multimodal Semantic Segmentation , 2018, International Journal of Computer Vision.