Singapore Institute of Technology
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Publications

  • Toward Scalable and Unified Example-Based Explanation and Outlier Detection
  • Resolving challenges in deep learning-based analyses of histopathological images using explanation methods
  • Beyond explaining: Opportunities and challenges of XAI-based model improvement
  • Discovering Transferable Forensic Features for CNN-generated Images Detection
  • To pretrain or not? A systematic analysis of the benefits of pretraining in diabetic retinopathy
  • Towards best practice in explaining neural network decisions with LRP
  • Exploring the Back Alleys: Analysing The Robustness of Alternative Neural Network Architectures against Adversarial Attacks
  • Generalized PatternAttribution for Neural Networks with Sigmoid Activations
  • BatchNorm Decomposition for Deep Neural Network Interpretation
  • Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification
  • Towards Best Practice in Explaining Neural Network Decisions with LRP
  • SmartOTPs: An Air-Gapped 2-Factor Authentication for Smart-Contract Wallets
  • SideInfNet: A Deep Neural Network for Semi-Automatic Semantic Segmentation with Side Information
  • Explanation-Guided Training for Cross-Domain Few-Shot Classification
  • Deep Semi-Supervised Anomaly Detection
  • Understanding Image Captioning Models beyond Visualizing Attention
  • SideInfNet: A Deep Neural Network for Semi-Automatic Semantic Segmentation with Side Information
  • Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin Images
  • Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification
  • Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution
  • Explain and improve: LRP-inference fine-tuning for image captioning models
  • Morphological and molecular breast cancer profiling through explainable machine learning
  • Beyond Explaining: Opportunities and Challenges of XAI-Based Model Improvement
  • Towards A Conceptually Simple Defensive Approach for Few-shot classifiers against Adversarial Support Samples
  • On the robustness of pretraining and self-supervision for a deep learning-based analysis of diabetic retinopathy
  • Detection of Adversarial Supports in Few-Shot Classifiers Using Self-Similarity and Filtering
  • Detection of adversarial supports in few-shot classifiers using self-similarity and filtering
  • Split and Expand: An inference-time improvement for Weakly Supervised Cell Instance Segmentation
  • Explanation-guided training for Cross-domain few-shot classification
  • Understanding integrated gradients with SmoothTaylor for deep neural network attribution
  • SideInfNet: A deep neural network for semi-automatic semantic segmentation with side information
  • Simple and effective prevention of mode collapse in deep one-class classification
  • Explain and improve: LRP-inference fine-tuning for image captioning models
  • DEEP SEMI-SUPERVISED ANOMALY DETECTION
  • Exploring the back alleys: Analysing the robustness of alternative neural network architectures against adversarial attacks
  • Deep semi-supervised anomaly detection
  • Adversarial Attacks on Remote User Authentication Using Behavioural Mouse Dynamics
  • To pretrain or not? A systematic analysis of the benefits of pretraining in diabetic retinopathy
  • Toward Scalable and Unified Example-based Explanation and Outlier Detection
  • OPTIMIZING EXPLANATIONS BY NETWORK CANONIZATION AND HYPERPARAMETER SEARCH
  • Explanation-guided training for cross-domain few-shot classification
  • Analysing the Adversarial Landscape of Binary Stochastic Networks
  • Discovering Transferable Forensic Features for CNN-generated Images Detection
  • Discovering Transferable Forensic Features for CNN-Generated Images Detection
  • Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations
  • Pruning by explaining: A novel criterion for deep neural network pruning
  • Adaptive noise injection for training stochastic student networks from deterministic teachers
  • Understanding integrated gradients with smoothtaylor for deep neural network attribution
  • User Authentication Based on Mouse Dynamics Using Deep Neural Networks: A Comprehensive Study
  • Adversarial Attacks on Remote User Authentication Using Behavioural Mouse Dynamics
  • Evaluating the Visualization of What a Deep Neural Network Has Learned
  • Learning and evaluation in presence of Non-i.i.d. label noise
  • ImageCLEF 2017: ImageCLEF tuberculosis task - The SGEast submission
  • The LRP toolbox for artificial neural networks
  • Multi-class SVMs: From tighter data-dependent generalization bounds to novel algorithms
  • Towards computational fluorescence microscopy: Machine learning-based integrated prediction of morphological and molecular tumor profiles
  • Relevance score assignment for artificial neural networks
  • Method and System for the Automatic Analysis of an Image of a Biological Sample
  • Localized multiple kernel learning—a convex approach
  • An Air-Gapped 2-Factor Authentication for Smart-Contract Wallets
  • Deep Taylor Decomposition of Neural Networks
  • Scoring of tumor-infiltrating lymphocytes: From visual estimation to machine learning
  • Theory and Algorithms for the Localized Setting of Learning Kernels
  • Analyzing and Validating Neural Networks Predictions
  • Localized multiple kernel learning|A convex approach
  • Mouse authentication without the temporal aspect - What does a 2D-CNN learn?
  • DeepClue: Visual Interpretation of Text-based Deep Stock Prediction
  • Thermal comfort based performance appraisal of covered walkways in Singapore
  • Bag of Machine Learning Concepts for Visual Concept Recognition in Images
  • Unmasking Clever Hans predictors and assessing what machines really learn
  • Deep one-class classification
  • Urban Zoning Using Higher-Order Markov Random Fields on Multi-View Imagery Data
  • Pruning by explaining: A novel criterion for deep neural network pruning
  • Towards best practice in explaining neural network decisions with LRP
  • Resolving challenges in deep learning-based analyses of histopathological images using explanation methods
  • Unmasking Clever Hans Predictors and Assessing What Machines Really Learn
  • SmartOTPs: An Air-Gapped 2-Factor Authentication for Smart-Contract Wallets
  • Towards computational fluorescence microscopy: Machine learning-based integrated prediction of morphological and molecular tumor profiles
  • Corplab Inli@FIRE-2018: Identification of indian native language using pairwise coupling
  • Understanding and comparing deep neural networks for age and gender classification
  • Layer-Wise Relevance Propagation: An Overview
  • Detection of masqueraders based on graph partitioning of file system access events
  • Memory snapshot dataset of a compromised host with malware using obfuscation evasion techniques
  • On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation
  • Machine Learning for Visual Concept Recognition and Ranking for Images
  • Identification of vehicle tracks and association to wireless endpoints by multiple sensor modalities
  • Multiple Kernel Learning for Brain-Computer Interfacing
  • Enhanced representation and multi-task learning for image annotation
  • Multi-modal identification and tracking of vehicles in partially observed environments
  • Layer-Wise Relevance Propagation for Deep Neural Network Architectures
  • Extracting latent brain states — Towards true labels in cognitive neuroscience experiments
  • When brain and behavior disagree: Tackling systematic label noise in EEG data with machine learning
  • Comparison of deep learning architectures for H&E histopathology images
  • Object Boundary Detection and Classification with Image-Level Labels
  • Understanding and Comparing Deep Neural Networks for Age and Gender Classification
  • Insights from curve fitting models in mouse dynamics authentication systems
  • Controlling explanatory heatmap resolution and semantics via decomposition depth
  • Analyzing Classifiers: Fisher Vectors and Deep Neural Networks
  • Layer-Wise Relevance Propagation for Neural Networks with Local Renormalization Layers
  • Explaining nonlinear classification decisions with deep Taylor decomposition
  • Efficient Classification of Images with Taxonomies
  • Shrinking large visual vocabularies using multi-label agglomerative information bottleneck
  • Enhancing Image Classification with Class-wise Clustered Vocabularies
  • B 17 Maschinelles Lernen, Mustererkennung in der Bildverarbeitung
  • Multi-task Learning via Non-sparse Multiple Kernel Learning
  • Enhancing Recognition of Visual Concepts with Primitive Color Histograms via Non-sparse Multiple Kernel Learning
  • A procedure of adaptive kernel combination with kernel-target alignment for object classification
  • On Taxonomies for Multi-class Image Categorization
  • Multi-modal visual concept classification of images via Markov random walk over tags
  • A Hybrid Supervised-Unsupervised Vocabulary Generation Algorithm for Visual Concept Recognition
  • Insights from Classifying Visual Concepts with Multiple Kernel Learning
  • Clinical relevance of CD95 (Fas/Apo-1) on T cells of patients with B-cell chronic lymphocytic leukemia
  • The Shogun machine learning toolbox
  • The joint submission of the TU Berlin and Fraunhofer FIRST (TUBFI) to the image CLEF 2011 photo annotation task
  • Fraunhofer FIRST's submission to ImageCLEF2009 photo annotation task: Non-sparse multiple kernel learning

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Nils Strodthoff

Nils Strodthoff

Alexander Binder's public data