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08/23/2023
Layer-wise Feedback Propagation
In this paper, we present Layer-wise Feedback Propagation (LFP), a novel...
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11/30/2022
Optimizing Explanations by Network Canonization and Hyperparameter Search
Explainable AI (XAI) is slowly becoming a key component for many AI appl...
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11/22/2022
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations
While the evaluation of explanations is an important step towards trustw...
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08/24/2022
Discovering Transferable Forensic Features for CNN-generated Images Detection
Visual counterfeits are increasingly causing an existential conundrum in...
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03/15/2022
Beyond Explaining: Opportunities and Challenges of XAI-Based Model Improvement
Explainable Artificial Intelligence (XAI) is an emerging research field ...
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10/24/2021
Towards A Conceptually Simple Defensive Approach for Few-shot classifiers Against Adversarial Support Samples
Few-shot classifiers have been shown to exhibit promising results in use...
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06/25/2021
On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy
There is an increasing number of medical use-cases where classification ...
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12/09/2020
Detection of Adversarial Supports in Few-shot Classifiers Using Feature Preserving Autoencoders and Self-Similarity
Few-shot classifiers excel under limited training samples, making it use...
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11/11/2020
Deja vu from the SVM Era: Example-based Explanations with Outlier Detection
Understanding the features that contributed to a prediction is important...
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07/21/2020
Lymphocyte counting – Error Analysis of Regression versus Bounding Box Detection Approaches
We consider the problem of counting cell nuclei from celltype-agnostic h...
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07/17/2020
Explanation-Guided Training for Cross-Domain Few-Shot Classification
Cross-domain few-shot classification task (CD-FSC) combines few-shot cla...
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04/22/2020
Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution
Integrated gradients as an attribution method for deep neural network mo...
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02/07/2020
SideInfNet: A Deep Neural Network for Semi-Automatic Semantic Segmentation with Side Information
Fully-automatic execution is the ultimate goal for many Computer Vision ...
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01/24/2020
Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification
Anomaly detection algorithms find extensive use in various fields. This ...
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01/04/2020
Understanding Image Captioning Models beyond Visualizing Attention
This paper explains predictions of image captioning models with attentio...
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12/08/2019
Exploring the Back Alleys: Analysing The Robustness of Alternative Neural Network Architectures against Adversarial Attacks
Recent discoveries in the field of adversarial machine learning have sho...
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10/22/2019
Towards best practice in explaining neural network decisions with LRP
Within the last decade, neural network based predictors have demonstrate...
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08/15/2019
Resolving challenges in deep learning-based analyses of histopathological images using explanation methods
Deep learning has recently gained popularity in digital pathology due to...
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06/06/2019
Deep Semi-Supervised Anomaly Detection
Deep approaches to anomaly detection have recently shown promising resul...
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05/28/2019
Adversarial Attacks on Remote User Authentication Using Behavioural Mouse Dynamics
Mouse dynamics is a potential means of authenticating users. Typically, ...
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02/26/2019
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn
Current learning machines have successfully solved hard application prob...
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12/10/2018
An Air-Gapped 2-Factor Authentication for Smart-Contract Wallets
With the recent rise of cryptocurrencies, the security and management of...
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05/28/2018
Towards computational fluorescence microscopy: Machine learning-based integrated prediction of morphological and molecular tumor profiles
Recent advances in cancer research largely rely on new developments in m...
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08/25/2017
Understanding and Comparing Deep Neural Networks for Age and Gender Classification
Recently, deep neural networks have demonstrated excellent performances ...
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06/29/2016
Object Boundary Detection and Classification with Image-level Labels
Semantic boundary and edge detection aims at simultaneously detecting ob...
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04/04/2016
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers
Layer-wise relevance propagation is a framework which allows to decompos...
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03/21/2016
Controlling Explanatory Heatmap Resolution and Semantics via Decomposition Depth
We present an application of the Layer-wise Relevance Propagation (LRP) ...
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12/08/2015
Explaining NonLinear Classification Decisions with Deep Taylor Decomposition
Nonlinear methods such as Deep Neural Networks (DNNs) are the gold stand...
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12/01/2015
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks
Fisher Vector classifiers and Deep Neural Networks (DNNs) are popular an...
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12/16/2011