Italy

ICPR 2020 is the premier international conference on Pattern Recognition, gathering leading researchers from around the world to present their latest achievements in Pattern Analysis and Recognition, applied Artificial Intelligence and Machine Learning. The topic of the year is " Putting Artificial intelligence to work on Patterns". 
For the first time, ICPR has employed a two-round review process similar to journal submissions, with new papers allowed to be submitted in either the first or second round and papers submitted in the first round and not accepted allowed to be revised and re-submitted for second round review. 

In this edition of the **ICPR 2020** Conference, there are 1407 Oral/Poster presentations organized in five Tracks: 
- Artificial Intelligence, Machine Learning for Pattern Analysis; 
- Biometrics, Human Analysis and Behavior Understanding; Computer Vision, Robotics and Intelligent Systems; 
- Document and Media Analysis; and 
- Image and Signal Processing. 

The **ICPR 2020** Main Conference program also includes 7 Keynotes from prominent world-renowned scientists, 8 Tutorials, 28 Demos, 8 Challenges, 2 Panels, as well as an Industry/Sponsor Exhibition. In addition, 41 Workshops on a range of important current and emerging research topics complete the ICPR 2020 program. 


ICPR 2020 MAIN CONFERENCE

To facilitate deep learning based table extraction from unstructured digital files, we disclose a standard Chinese financial dataset from PDF files for table extraction benchmark test, which is diverse, sufficient and comprehensive. We also propose a GCN-based algorithm GFTE as a baseline with a novel idea of integrating all possible types of ground truth together.

GFTE: Graph-based Financial Table Extraction

technical paper

Relative Attribute Classification with Deep-RankSVM

Recursive Division of Image for Explanation of Shallow CNN Models

Samples Classification Analysis Across DNN Layers with Fractal Curves

Explaining How Deep Neural Networks Forget by Deep Visualization

The Impact of Activation Sparsity on Overfitting in Convolutional Neural Networks

A Multi-layered Approach for Tailored Black-box Explanations

Explanation-driven Characterization of Android Ransomware

Post-Hoc Explanation Options for XAI in Deep Learning: The Insight Centre for Data Analytics Perspective

Jointly Optimize Positive and Negative Saliencies for Black Box Classifiers

Deep Learning for Astrophysics, Understanding the Impact of Attention on Variability Induced by Parameter Initialization

poster

Premium content

GFTE: Graph-based Financial Table Extraction

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Relative Attribute Classification with Deep-RankSVM

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