Artificial neural networks in pattern recognition : 9th IAPR TC3 Workshop, ANNPR 2020, Winterthur, Switzerland, September 2-4, 2020, Proceedings /: 9th IAPR TC3 Workshop, ANNPR 2020, Winterthur, Switzerland, September 2-4, 2020, Proceedings. (2020)

• Record Type: Book
• Other Titles: ANNPR 2020
• Further Information: Note: Frank-Peter Schilling, Thilo Stadelmann (eds.).
• Other Names: Schilling, F.-P (Frank-Peter); Stadelmann, Thilo; ANNPR (Workshop), 9th
• Contents: Intro -- Preface -- Organization -- Contents -- Invited Papers -- Deep Learning Methods for Image Guidance in Radiation Therapy -- 1 Introduction -- 2 Motion Monitoring During Treatment -- 2.1 Tracking of Bony Structures -- 2.2 Soft Tissue Tracking -- 3 CBCT Image Reconstruction -- 3.1 X-ray Projection Pre-processing -- 3.2 CBCT Volume Post-processing -- 3.3 Iterative CBCT Reconstruction Methods -- 3.4 End-to-End CBCT Image Reconstruction Learning -- 3.5 4D CBCT Reconstruction -- 4 Deep Learning for Organ Segmentation -- 5 Deformable Image Registration -- 6 Conclusion -- References Intentional Image Similarity Search -- 1 Introduction -- 2 Related Work -- 3 German Broadcasting Archive -- 4 A Novel Approach to Intentional Image Similarity Search -- 4.1 Query Specification -- 4.2 Hybrid Feature Method -- 4.3 Plugin Mechanism -- 5 Experimental Results -- 6 Conclusion -- References -- Foundations -- Structured (De)composable Representations Trained with Neural Networks -- 1 Introduction -- 2 Background -- 3 CoDiR: Method -- 4 Experiments -- 4.1 Setup -- 4.2 Results -- 5 Conclusion -- References Long Distance Relationships Without Time Travel: Boosting the Performance of a Sparse Predictive Autoencoder in Sequence Modeling -- 1 Introduction -- 1.1 Motivation -- 2 Method -- 2.1 Original RSM Model -- 2.2 Boosted RSM (bRSM) -- 3 Experiments -- 3.1 Stochastic Sequential MNIST (ssMNIST) -- 3.2 Language Modeling -- 4 Conclusion -- References -- Improving Accuracy and Efficiency of Object Detection Algorithms Using Multiscale Feature Aggregation Plugins -- 1 Introduction -- 2 Proposed Approach -- 2.1 Motivating the Need of Feature-Fusion 2.2 Implementing Aggregation Plugins in SSD-VGG16 Model -- 3 Results and Analysis -- 3.1 Experimental Platform -- 3.2 Results -- 4 Conclusion -- References -- Abstract Echo State Networks -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Local Robustness -- 3.2 Abstract Interpretation -- 3.3 Echo State Networks -- 3.4 Abstract Training -- 3.5 Experiment -- 4 Results and Discussion -- 5 Conclusion -- References -- Minimal Complexity Support Vector Machines -- 1 Introduction -- 2 L1 Support Vector Machines and Minimal Complexity Machines -- 2.1 L1 Support Vector Machines 2.2 Minimal Complexity Machines -- 3 Minimal Complexity L1 Support Vector Machines -- 3.1 Architecture -- 3.2 KKT Conditions -- 3.3 Variant of Minimal Complexity Support Vector Machines -- 4 Computer Experiments -- 4.1 Comparison Conditions -- 4.2 Two-Class Problems -- 4.3 Multiclass Problems -- 5 Conclusions -- References -- Named Entity Disambiguation at Scale -- 1 Introduction -- 2 Related Work -- 3 Model Description -- 4 Experimental Results -- 5 Ablation -- 6 Conclusion -- References -- Applications -- Geometric Attention for Prediction of Differential Properties in 3D Point Clouds
• Publisher Details: Cham, Switzerland : Springer
• Publication Date: 2020
• Extent: 1 online resource
• Subjects: 006.3/2; Neural networks (Computer science) -- Congresses; Pattern recognition systems -- Congresses; Electronic books; Electronic books
• Languages: English
• ISBNs: 9783030583095; 3030583090
• Related ISBNs: 9783030583088; 3030583082
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