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ORCIDAlexander Binder
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- affiliation: Technical University of Berlin, Department of Mathematics, Germany
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Books and Theses
- 2013
[b1]Alexander Binder:
Bag of Machine Learning Concepts for Visual Concept Recognition in Images. Berlin Institute of Technology, 2013
Journal Articles
- 2023
- [j14]Leander Weber
, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek:
Beyond explaining: Opportunities and challenges of XAI-based model improvement. Inf. Fusion 92: 154-176 (2023) - 2022
- [j13]Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Alexander Binder:
Explain and improve: LRP-inference fine-tuning for image captioning models. Inf. Fusion 77: 233-246 (2022) - [j12]Penny Chong, Ngai-Man Cheung, Yuval Elovici, Alexander Binder:
Toward Scalable and Unified Example-Based Explanation and Outlier Detection. IEEE Trans. Image Process. 31: 525-540 (2022) - 2021
- [j11]Alexander Binder, Michael Bockmayr, Miriam Hägele, Stephan Wienert, Daniel Heim, Katharina Hellweg, Masaru Ishii, Albrecht Stenzinger, Andreas Hocke, Carsten Denkert, Klaus-Robert Müller, Frederick Klauschen:
Morphological and molecular breast cancer profiling through explainable machine learning. Nat. Mach. Intell. 3(4): 355-366 (2021) - [j10]Seul-Ki Yeom, Philipp Seegerer, Sebastian Lapuschkin, Alexander Binder, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Pruning by explaining: A novel criterion for deep neural network pruning. Pattern Recognit. 115: 107899 (2021) - 2020
- [j9]Penny Chong, Yuval Elovici, Alexander Binder:
User Authentication Based on Mouse Dynamics Using Deep Neural Networks: A Comprehensive Study. IEEE Trans. Inf. Forensics Secur. 15: 1086-1101 (2020) - 2019
- [j8]Lei Shi, Zhiyang Teng, Le Wang, Yue Zhang, Alexander Binder:
DeepClue: Visual Interpretation of Text-Based Deep Stock Prediction. IEEE Trans. Knowl. Data Eng. 31(6): 1094-1108 (2019) - 2017
- [j7]Grégoire Montavon, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek, Klaus-Robert Müller:
Explaining nonlinear classification decisions with deep Taylor decomposition. Pattern Recognit. 65: 211-222 (2017) - [j6]Wojciech Samek, Alexander Binder, Grégoire Montavon, Sebastian Lapuschkin, Klaus-Robert Müller:
Evaluating the Visualization of What a Deep Neural Network Has Learned. IEEE Trans. Neural Networks Learn. Syst. 28(11): 2660-2673 (2017) - 2016
- [j5]Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
The LRP Toolbox for Artificial Neural Networks. J. Mach. Learn. Res. 17: 114:1-114:5 (2016) - 2015
- [j4]Anne K. Porbadnigk, Nico Görnitz, Claudia Sannelli, Alexander Binder, Mikio L. Braun, Marius Kloft, Klaus-Robert Müller:
Extracting latent brain states - Towards true labels in cognitive neuroscience experiments. NeuroImage 120: 225-253 (2015) - 2013
- [j3]Alexander Binder, Wojciech Samek, Klaus-Robert Müller, Motoaki Kawanabe:
Enhanced representation and multi-task learning for image annotation. Comput. Vis. Image Underst. 117(5): 466-478 (2013) - 2012
- [j2]Alexander Binder, Klaus-Robert Müller, Motoaki Kawanabe:
On Taxonomies for Multi-class Image Categorization. Int. J. Comput. Vis. 99(3): 281-301 (2012) - 2010
- [j1]Sören Sonnenburg, Gunnar Rätsch, Sebastian Henschel, Christian Widmer, Jonas Behr, Alexander Zien, Fabio De Bona, Alexander Binder, Christian Gehl, Vojtech Franc:
The SHOGUN Machine Learning Toolbox. J. Mach. Learn. Res. 11: 1799-1802 (2010)
Conference and Workshop Papers
- 2023
- [c43]Frederik Pahde, Galip Ümit Yolcu, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin:
Optimizing Explanations by Network Canonization and Hyperparameter Search. CVPR Workshops 2023: 3819-3828 - [c42]Alexander Binder, Leander Weber, Sebastian Lapuschkin, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations. CVPR 2023: 16143-16152 - 2022
- [c41]Keshigeyan Chandrasegaran, Ngoc-Trung Tran, Alexander Binder, Ngai-Man Cheung:
Discovering Transferable Forensic Features for CNN-Generated Images Detection. ECCV (15) 2022: 671-689 - 2020
- [c40]Ivan Homoliak, Dominik Breitenbacher, Ondrej Hujnak, Pieter H. Hartel, Alexander Binder, Pawel Szalachowski:
SmartOTPs: An Air-Gapped 2-Factor Authentication for Smart-Contract Wallets. AFT 2020: 145-162 - [c39]Jing Yu Koh, Duc Thanh Nguyen, Quang-Trung Truong, Sai-Kit Yeung, Alexander Binder:
SideInfNet: A Deep Neural Network for Semi-Automatic Semantic Segmentation with Side Information. ECCV (24) 2020: 103-118 - [c38]Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft:
Deep Semi-Supervised Anomaly Detection. ICLR 2020 - [c37]Gary S. W. Goh, Sebastian Lapuschkin, Leander Weber, Wojciech Samek, Alexander Binder:
Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution. ICPR 2020: 4949-4956 - [c36]Yi Xiang Marcus Tan, Yuval Elovici, Alexander Binder:
Adaptive Noise Injection for Training Stochastic Student Networks from Deterministic Teachers. ICPR 2020: 7587-7594 - [c35]Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Yunqing Zhao, Ngai-Man Cheung, Alexander Binder:
Explanation-Guided Training for Cross-Domain Few-Shot Classification. ICPR 2020: 7609-7616 - [c34]Penny Chong, Lukas Ruff, Marius Kloft, Alexander Binder:
Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification. IJCNN 2020: 1-9 - [c33]Maximilian Kohlbrenner, Alexander Bauer, Shinichi Nakajima, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin:
Towards Best Practice in Explaining Neural Network Decisions with LRP. IJCNN 2020: 1-7 - 2019
- [c32]Jiamei Sun, Alexander Binder:
Generalized PatternAttribution for Neural Networks with Sigmoid Activations. IJCNN 2019: 1-9 - [c31]Yi Xiang Marcus Tan, Alfonso Iacovazzi, Ivan Homoliak, Yuval Elovici, Alexander Binder:
Adversarial Attacks on Remote User Authentication Using Behavioural Mouse Dynamics. IJCNN 2019: 1-10 - [c30]Lucas Y. W. Hui, Alexander Binder:
BatchNorm Decomposition for Deep Neural Network Interpretation. IWANN (2) 2019: 280-291 - 2018
- [c29]Tian Feng, Quang-Trung Truong, Duc Thanh Nguyen, Jing Yu Koh, Lap-Fai Yu, Alexander Binder, Sai-Kit Yeung:
Urban Zoning Using Higher-Order Markov Random Fields on Multi-View Imagery Data. ECCV (8) 2018: 627-644 - [c28]Soumik Mondal, Athul Harilal, Alexander Binder:
Corplab INLI@FIRE-2018: Identification of Indian Native Language using Pairwise Coupling. FIRE (Working Notes) 2018: 77-81 - [c27]Lukas Ruff, Nico Görnitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Robert A. Vandermeulen, Alexander Binder, Emmanuel Müller, Marius Kloft:
Deep One-Class Classification. ICML 2018: 4390-4399 - [c26]Penny Chong, Yi Xiang Marcus Tan, Juan Guarnizo, Yuval Elovici, Alexander Binder:
Mouse Authentication Without the Temporal Aspect - What Does a 2D-CNN Learn? IEEE Symposium on Security and Privacy Workshops 2018: 15-21 - [c25]Flavio Toffalini, Ivan Homoliak, Athul Harilal, Alexander Binder, Martín Ochoa:
Detection of Masqueraders Based on Graph Partitioning of File System Access Events. IEEE Symposium on Security and Privacy Workshops 2018: 217-227 - 2017
- [c24]Jiamei Sun, Penny Chong, Yi Xiang Marcus Tan, Alexander Binder:
ImageCLEF 2017: ImageCLEF Tuberculosis Task - the SGEast Submission. CLEF (Working Notes) 2017 - [c23]Jing Yu Koh, Wojciech Samek, Klaus-Robert Müller, Alexander Binder:
Object Boundary Detection and Classification with Image-Level Labels. GCPR 2017: 153-164 - [c22]Wojciech Samek, Alexander Binder, Sebastian Lapuschkin, Klaus-Robert Müller:
Understanding and Comparing Deep Neural Networks for Age and Gender Classification. ICCV Workshops 2017: 1629-1638 - 2016
- [c21]Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft:
Localized Multiple Kernel Learning - A Convex Approach. ACML 2016: 81-96 - [c20]Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. CVPR 2016: 2912-2920 - [c19]Alexander Binder, Grégoire Montavon, Sebastian Lapuschkin, Klaus-Robert Müller, Wojciech Samek:
Layer-Wise Relevance Propagation for Neural Networks with Local Renormalization Layers. ICANN (2) 2016: 63-71 - [c18]Sebastian Bach, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
Controlling explanatory heatmap resolution and semantics via decomposition depth. ICIP 2016: 2271-2275 - 2015
- [c17]Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft:
Theory and Algorithms for the Localized Setting of Learning Kernels. FE@NIPS 2015: 173-195 - [c16]Yunwen Lei, Ürün Dogan, Alexander Binder, Marius Kloft:
Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms. NIPS 2015: 2035-2043 - 2014
- [c15]Nico Görnitz, Anne Porbadnigk, Alexander Binder, Claudia Sannelli, Mikio L. Braun, Klaus-Robert Müller, Marius Kloft:
Learning and Evaluation in Presence of Non-i.i.d. Label Noise. AISTATS 2014: 293-302 - [c14]Anne K. Porbadnigk, Nico Görnitz, Claudia Sannelli, Alexander Binder, Mikio L. Braun, Marius Kloft, Klaus-Robert Müller:
When brain and behavior disagree: Tackling systematic label noise in EEG data with machine learning. BCI 2014: 1-4 - [c13]Daniel Becker, Alexander Binder, Jens Einsiedler, Ilja Radusch:
Multi-modal identification and tracking of vehicles in partially observed environments. IPIN 2014: 77-86 - 2013
- [c12]Wojciech Samek, Alexander Binder, Klaus-Robert Müller:
Multiple Kernel Learning for Brain-Computer Interfacing. EMBC 2013: 7048-7051 - [c11]Daniel Becker, Jens Einsiedler, Bernd Schäufele, Alexander Binder, Ilja Radusch:
Identification of vehicle tracks and association to wireless endpoints by multiple sensor modalities. IPIN 2013: 1-10 - 2011
- [c10]Wojciech Samek, Alexander Binder, Motoaki Kawanabe:
Multi-task Learning via Non-sparse Multiple Kernel Learning. CAIP (1) 2011: 335-342 - [c9]Alexander Binder, Wojciech Samek, Marius Kloft, Christina Müller, Klaus-Robert Müller, Motoaki Kawanabe:
The Joint Submission of the TU Berlin and Fraunhofer FIRST (TUBFI) to the ImageCLEF2011 Photo Annotation Task. CLEF (Notebook Papers/Labs/Workshop) 2011 - [c8]Motoaki Kawanabe, Alexander Binder, Christina Müller, Wojciech Wojcikiewicz:
Multi-modal visual concept classification of images via Markov random walk over tags. WACV 2011: 396-401 - 2010
- [c7]Alexander Binder, Wojciech Wojcikiewicz, Christina Müller, Motoaki Kawanabe:
A Hybrid Supervised-Unsupervised Vocabulary Generation Algorithm for Visual Concept Recognition. ACCV (3) 2010: 95-108 - [c6]Wojciech Wojcikiewicz, Alexander Binder, Motoaki Kawanabe:
Shrinking large visual vocabularies using multi-label agglomerative information bottleneck. ICIP 2010: 3849-3852 - [c5]Wojciech Wojcikiewicz, Alexander Binder, Motoaki Kawanabe:
Enhancing Image Classification with Class-wise Clustered Vocabularies. ICPR 2010: 1060-1063 - 2009
- [c4]Alexander Binder, Motoaki Kawanabe, Ulf Brefeld:
Efficient Classification of Images with Taxonomies. ACCV (3) 2009: 351-362 - [c3]Motoaki Kawanabe, Shinichi Nakajima, Alexander Binder:
A procedure of adaptive kernel combination with kernel-target alignment for object classification. CIVR 2009 - [c2]Alexander Binder, Motoaki Kawanabe:
Enhancing Recognition of Visual Concepts with Primitive Color Histograms via Non-sparse Multiple Kernel Learning. CLEF (2) 2009: 269-276 - [c1]Alexander Binder, Motoaki Kawanabe:
Fraunhofer FIRST's Submission to ImageCLEF2009 Photo Annotation Task: Non-sparse Multiple Kernel Learning. CLEF (Working Notes) 2009
Parts in Books or Collections
- 2020
- [p3]Philipp Seegerer, Alexander Binder, René Saitenmacher, Michael Bockmayr, Maximilian Alber, Philipp Jurmeister, Frederick Klauschen, Klaus-Robert Müller:
Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin Images. AI and ML for Digital Pathology 2020: 16-37 - 2019
- [p2]Grégoire Montavon, Alexander Binder, Sebastian Lapuschkin, Wojciech Samek, Klaus-Robert Müller:
Layer-Wise Relevance Propagation: An Overview. Explainable AI 2019: 193-209 - 2014
- [p1]Alexander Binder, Wojciech Samek, Klaus-Robert Müller, Motoaki Kawanabe:
Machine Learning for Visual Concept Recognition and Ranking for Images. Towards the Internet of Services 2014: 211-223
Informal and Other Publications
- 2023
- [i34]Leander Weber, Jim Berend, Alexander Binder, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
Layer-wise Feedback Propagation. CoRR abs/2308.12053 (2023) - 2022
- [i33]Leander Weber, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek:
Beyond Explaining: Opportunities and Challenges of XAI-Based Model Improvement. CoRR abs/2203.08008 (2022) - [i32]Keshigeyan Chandrasegaran, Ngoc-Trung Tran, Alexander Binder, Ngai-Man Cheung:
Discovering Transferable Forensic Features for CNN-generated Images Detection. CoRR abs/2208.11342 (2022) - [i31]Alexander Binder, Leander Weber, Sebastian Lapuschkin, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations. CoRR abs/2211.12486 (2022) - [i30]Frederik Pahde, Galip Ümit Yolcu, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin:
Optimizing Explanations by Network Canonization and Hyperparameter Search. CoRR abs/2211.17174 (2022) - 2021
- [i29]Vignesh Srinivasan, Nils Strodthoff, Jackie Ma, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy. CoRR abs/2106.13497 (2021) - [i28]Yi Xiang Marcus Tan, Penny Chong, Jiamei Sun, Ngai-Man Cheung, Yuval Elovici, Alexander Binder:
Towards A Conceptually Simple Defensive Approach for Few-shot classifiers Against Adversarial Support Samples. CoRR abs/2110.12357 (2021) - 2020
- [i27]Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Alexander Binder:
Understanding Image Captioning Models beyond Visualizing Attention. CoRR abs/2001.01037 (2020) - [i26]Penny Chong, Lukas Ruff, Marius Kloft, Alexander Binder:
Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification. CoRR abs/2001.08873 (2020) - [i25]Jing Yu Koh, Duc Thanh Nguyen, Quang-Trung Truong, Sai-Kit Yeung, Alexander Binder:
SideInfNet: A Deep Neural Network for Semi-Automatic Semantic Segmentation with Side Information. CoRR abs/2002.02634 (2020) - [i24]Gary S. W. Goh, Sebastian Lapuschkin, Leander Weber, Wojciech Samek, Alexander Binder:
Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution. CoRR abs/2004.10484 (2020) - [i23]Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Yunqing Zhao, Ngai-Man Cheung, Alexander Binder:
Explanation-Guided Training for Cross-Domain Few-Shot Classification. CoRR abs/2007.08790 (2020) - [i22]Lin Geng Foo, Alexander Binder:
Lymphocyte counting - Error Analysis of Regression versus Bounding Box Detection Approaches. CoRR abs/2007.10817 (2020) - [i21]Penny Chong, Yuval Elovici, Alexander Binder:
Deja vu from the SVM Era: Example-based Explanations with Outlier Detection. CoRR abs/2011.05577 (2020) - [i20]Yi Xiang Marcus Tan, Penny Chong, Jiamei Sun, Yuval Elovici, Alexander Binder:
Detection of Adversarial Supports in Few-shot Classifiers Using Feature Preserving Autoencoders and Self-Similarity. CoRR abs/2012.06330 (2020) - 2019
- [i19]Sebastian Lapuschkin, Stephan Wäldchen, Alexander Binder, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller:
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn. CoRR abs/1902.10178 (2019) - [i18]Yi Xiang Marcus Tan, Alfonso Iacovazzi, Ivan Homoliak, Yuval Elovici, Alexander Binder:
Adversarial Attacks on Remote User Authentication Using Behavioural Mouse Dynamics. CoRR abs/1905.11831 (2019) - [i17]Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft:
Deep Semi-Supervised Anomaly Detection. CoRR abs/1906.02694 (2019) - [i16]Miriam Hägele, Philipp Seegerer, Sebastian Lapuschkin, Michael Bockmayr, Wojciech Samek, Frederick Klauschen, Klaus-Robert Müller, Alexander Binder:
Resolving challenges in deep learning-based analyses of histopathological images using explanation methods. CoRR abs/1908.06943 (2019) - [i15]Maximilian Kohlbrenner, Alexander Bauer, Shinichi Nakajima, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin:
Towards best practice in explaining neural network decisions with LRP. CoRR abs/1910.09840 (2019) - [i14]Yi Xiang Marcus Tan, Yuval Elovici, Alexander Binder:
Exploring the Back Alleys: Analysing The Robustness of Alternative Neural Network Architectures against Adversarial Attacks. CoRR abs/1912.03609 (2019) - 2018
- [i13]Alexander Binder, Michael Bockmayr, Miriam Hägele, Stephan Wienert, Daniel Heim, Katharina Hellweg, Albrecht Stenzinger, Laura Parlow, Jan Budczies, Benjamin Goeppert, Denise Treue, Manato Kotani, Masaru Ishii, Manfred Dietel, Andreas Hocke, Carsten Denkert, Klaus-Robert Müller, Frederick Klauschen:
Towards computational fluorescence microscopy: Machine learning-based integrated prediction of morphological and molecular tumor profiles. CoRR abs/1805.11178 (2018) - [i12]Ivan Homoliak, Dominik Breitenbacher, Alexander Binder, Pawel Szalachowski:
An Air-Gapped 2-Factor Authentication for Smart-Contract Wallets. CoRR abs/1812.03598 (2018) - 2017
- [i11]Sebastian Lapuschkin, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
Understanding and Comparing Deep Neural Networks for Age and Gender Classification. CoRR abs/1708.07689 (2017) - 2016
- [i10]Sebastian Bach, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
Controlling Explanatory Heatmap Resolution and Semantics via Decomposition Depth. CoRR abs/1603.06463 (2016) - [i9]Alexander Binder, Grégoire Montavon, Sebastian Bach, Klaus-Robert Müller, Wojciech Samek:
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers. CoRR abs/1604.00825 (2016) - [i8]Jing Yu Koh, Wojciech Samek, Klaus-Robert Müller, Alexander Binder:
Zero Shot Learning for Semantic Boundary Detection - How Far Can We Get? CoRR abs/1606.09187 (2016) - [i7]Wojciech Samek, Grégoire Montavon, Alexander Binder, Sebastian Lapuschkin, Klaus-Robert Müller:
Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation. CoRR abs/1611.08191 (2016) - 2015
- [i6]Yunwen Lei, Ürün Dogan, Alexander Binder, Marius Kloft:
Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms. CoRR abs/1506.04359 (2015) - [i5]Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft:
Localized Multiple Kernel Learning - A Convex Approach. CoRR abs/1506.04364 (2015) - [i4]Wojciech Samek, Alexander Binder, Grégoire Montavon, Sebastian Bach, Klaus-Robert Müller:
Evaluating the visualization of what a Deep Neural Network has learned. CoRR abs/1509.06321 (2015) - [i3]Sebastian Bach, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. CoRR abs/1512.00172 (2015) - [i2]Grégoire Montavon, Sebastian Bach, Alexander Binder, Wojciech Samek, Klaus-Robert Müller:
Explaining NonLinear Classification Decisions with Deep Taylor Decomposition. CoRR abs/1512.02479 (2015) - 2011
- [i1]Alexander Binder, Shinichi Nakajima, Marius Kloft, Christina Müller, Wojciech Samek, Ulf Brefeld, Klaus-Robert Müller, Motoaki Kawanabe:
Insights from Classifying Visual Concepts with Multiple Kernel Learning. CoRR abs/1112.3697 (2011)
Coauthor Index
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