Intro
Preface
Organization
The Fuzzy Boundaries of Reproducibility (Lightweight Presentation Abstract)
Contents
Reproducible Research Framework
Development Efforts for Reproducible Research: Platform, Library and Editorial Investment
1 Introduction
2 Reproducible Research Platform Updates
3 Reproducible Research Through Libraries
3.1 Library Experiences from Pattern Recognition, Image and Geometry Domains
3.2 Higra Library Development Feedback
4 Advanced Editorial Efforts
4.1 Improvements in the IPOL Journal

4.2 OVD-SaaS, a Spin-Off of IPOL for Industrial Applications
5 Conclusion
References
Reproducible Research Results
Enhancing GNN Feature Modeling for Document Information Extraction Using Transformers
1 Introduction
2 Related Works
3 Proposed Model
3.1 Texts and Bounding Boxes
3.2 Features Assignment
3.3 Graph Construction
3.4 GNN Model
3.5 Model Prediction
4 Experiments
4.1 Dataset
4.2 Experimental Setup
4.3 Metrics
4.4 Results
4.5 Implementation Details
5 Conclusion
References
Short ICPR Companion Papers

A Novel Pattern-Based Edit Distance for Automatic Log Parsing: Implementation and Reproducibility Notes
1 Introduction
2 Implementation Considerations
3 Installation Steps
4 Pattern Clustering Usage
4.1 Pattern Collection
4.2 Returned Value
4.3 Dropping Duplicated Pattern Automata
5 Experimental Setup
5.1 Drain and LogMine Integration
5.2 Loghub Dataset
5.3 Ground Truth
5.4 Experimental Parameters
5.5 Accuracy
6 Conclusion
References
Companion Paper: Deep Saliency Map Generators for Multispectral Video Classification
1 Introduction

2 Deep Saliency Map Generators
2.1 Grad-CAM
2.2 RISE
2.3 SIDU
3 Networks
3.1 3D-ResNet
3.2 Persistent Appearance Network
4 Evaluation
4.1 Deletion Metric
4.2 Insertion Metric
5 Conclusion
References
On Challenging Aspects of Reproducibility in Deep Anomaly Detection
1 Introduction
2 Deep Anomaly Detection
3 Challenges for Reproducibility
3.1 Nondeterminism in Network Optimization
3.2 Sensitivity to Hyperparameters
3.3 Complexity
3.4 Dataset Selection
3.5 Resource Limitations
3.6 Dependencies
4 Complexity-Evidence Tradeoff

5 Conclusion
References
On the Implementation of Baselines and Lightweight Conditional Model Extrapolation (LIMES) Under Class-Prior Shift
1 Introduction
2 Dataset
3 Implementation
3.1 Preprocessing of Raw Json Files with Twitter Data
3.2 Embeddings
3.3 Machine Learning Models
Training and Evaluation
3.4 Running Experiments Efficiently
4 Reproducibility
5 Credibility of Results
6 Conclusions
References
Special Reproducibility Track from DGMM Event
Combining Max-Tree and CNN for Segmentation of Cellular FIB-SEM Images
1 Introduction