128 citations · 139 across the 12 of their papers we have counts for
6 papers · 1 filter
Quantile-based Maximum Likelihood Training for Outlier Detection
Masoud Taghikhah, Nishant Kumar, Siniša Šegvić +2
Discriminative learning effectively predicts true object class for image classification. However, it often results in false positives for outliers, posing critical concerns in appl…
Uncertainty Quantification for Image-based Traffic Prediction across Cities
Alexander Timans, Nina Wiedemann, Nishant Kumar +2
Despite the strong predictive performance of deep learning models for traffic prediction, their widespread deployment in real-world intelligent transportation systems has been rest…
Normalizing Flow based Feature Synthesis for Outlier-Aware Object Detection
Nishant Kumar, Siniša Šegvić, Abouzar Eslami +1
Real-world deployment of reliable object detectors is crucial for applications such as autonomous driving. However, general-purpose object detectors like Faster R-CNN are prone to…
Enhancing Fairness of Visual Attribute Predictors
Tobias Hänel, Nishant Kumar, Dmitrij Schlesinger +4
The performance of deep neural networks for image recognition tasks such as predicting a smiling face is known to degrade with under-represented classes of sensitive attributes. We…
FuseVis: Interpreting neural networks for image fusion using per-pixel saliency visualization
Nishant Kumar, Stefan Gumhold
Image fusion helps in merging two or more images to construct a more informative single fused image. Recently, unsupervised learning based convolutional neural networks (CNN) have…
Visualisation of Medical Image Fusion and Translation for Accurate Diagnosis of High Grade Gliomas
Nishant Kumar, Nico Hoffmann, Matthias Kirsch +1
The medical image fusion combines two or more modalities into a single view while medical image translation synthesizes new images and assists in data augmentation. Together, these…