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Nikhil Kapoor
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2020 – today
- 2023
- [c6]Dominik Werner Wolf, Markus Ulrich, Nikhil Kapoor:
Sensitivity analysis of AI-based algorithms for autonomous driving on optical wavefront aberrations induced by the windshield. ICCV (Workshops) 2023: 4102-4111 - [i7]Dominik Werner Wolf, Markus Ulrich, Nikhil Kapoor:
Sensitivity analysis of AI-based algorithms for autonomous driving on optical wavefront aberrations induced by the windshield. CoRR abs/2308.11711 (2023) - 2022
- [c5]Rushil Gupta, Suryateja BV, Nikhil Kapoor, Rajat Jaiswal, Sharmila Nangi, Kuldeep Kulkarni:
User-Guided Variable Rate Learned Image Compression. CVPR Workshops 2022: 1752-1757 - 2021
- [j1]Andreas Bär, Jonas Löhdefink, Nikhil Kapoor, Serin Varghese, Fabian Hüger, Peter Schlicht, Tim Fingscheidt:
The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing. IEEE Signal Process. Mag. 38(1): 42-52 (2021) - [c4]Serin Varghese, Sharat Gujamagadi, Marvin Klingner, Nikhil Kapoor, Andreas Bär, Jan David Schneider, Kira Maag, Peter Schlicht, Fabian Hüger, Tim Fingscheidt:
An Unsupervised Temporal Consistency (TC) Loss To Improve the Performance of Semantic Segmentation Networks. CVPR Workshops 2021: 12-20 - [c3]Nikhil Kapoor, Andreas Bär, Serin Varghese, Jan David Schneider, Fabian Hüger, Peter Schlicht, Tim Fingscheidt:
From a Fourier-Domain Perspective on Adversarial Examples to a Wiener Filter Defense for Semantic Segmentation. IJCNN 2021: 1-8 - [i6]Andreas Bär, Jonas Löhdefink, Nikhil Kapoor, Serin J. Varghese, Fabian Hüger, Peter Schlicht, Tim Fingscheidt:
The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing. CoRR abs/2101.03924 (2021) - [i5]Sebastian Houben, Stephanie Abrecht, Maram Akila, Andreas Bär, Felix Brockherde, Patrick Feifel, Tim Fingscheidt, Sujan Sai Gannamaneni, Seyed Eghbal Ghobadi, Ahmed Hammam, Anselm Haselhoff, Felix Hauser, Christian Heinzemann, Marco Hoffmann, Nikhil Kapoor, Falk Kappel, Marvin Klingner, Jan Kronenberger, Fabian Küppers, Jonas Löhdefink, Michael Mlynarski, Michael Mock, Firas Mualla, Svetlana Pavlitskaya, Maximilian Poretschkin, Alexander Pohl, Varun Ravi Kumar, Julia Rosenzweig, Matthias Rottmann, Stefan Rüping, Timo Sämann, Jan David Schneider, Elena Schulz, Gesina Schwalbe, Joachim Sicking, Toshika Srivastava, Serin Varghese, Michael Weber, Sebastian Wirkert, Tim Wirtz, Matthias Woehrle:
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety. CoRR abs/2104.14235 (2021) - 2020
- [c2]Nikhil Kapoor, Chun Yuan, Jonas Löhdefink, Roland Zimmermann, Serin Varghese, Fabian Hüger, Nico M. Schmidt, Peter Schlicht, Tim Fingscheidt:
A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs. CSCS 2020: 3:1-3:8 - [c1]Serin Varghese, Yasin Bayzidi, Andreas Bär, Nikhil Kapoor, Sounak Lahiri, Jan David Schneider, Nico M. Schmidt, Peter Schlicht, Fabian Hüger, Tim Fingscheidt:
Unsupervised Temporal Consistency Metric for Video Segmentation in Highly-Automated Driving. CVPR Workshops 2020: 1369-1378 - [i4]Paul Schwerdtner, Florens Greßner, Nikhil Kapoor, Felix Assion, René Sass, Wiebke Günther, Fabian Hüger, Peter Schlicht:
Risk Assessment for Machine Learning Models. CoRR abs/2011.04328 (2020) - [i3]Nikhil Kapoor, Chun Yuan, Jonas Löhdefink, Roland Zimmermann, Serin Varghese, Fabian Hüger, Nico M. Schmidt, Peter Schlicht, Tim Fingscheidt:
A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs. CoRR abs/2012.01386 (2020) - [i2]Nikhil Kapoor, Andreas Bär, Serin Varghese, Jan David Schneider, Fabian Hüger, Peter Schlicht, Tim Fingscheidt:
From a Fourier-Domain Perspective on Adversarial Examples to a Wiener Filter Defense for Semantic Segmentation. CoRR abs/2012.01558 (2020)
2000 – 2009
- 2009
- [i1]Durgesh Kumar Mishra, Neha Koria, Nikhil Kapoor, Ravish Bahety:
A Secure Multi-Party Computation Protocol for Malicious Computation Prevention for preserving privacy during Data Mining. CoRR abs/0908.0994 (2009)
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