Chaithanya Kumar Mummadi
Chaithanya Kumar Mummadi
Machine Learning Research Scientist, Bosch Center for Artificial Intelligence, Robert Bosch LLC, USA
Verified email at
Cited by
Cited by
Universal adversarial perturbations against semantic image segmentation
J Hendrik Metzen, M Chaithanya Kumar, T Brox, V Fischer
Proceedings of the IEEE international conference on computer vision, 2755-2764, 2017
Self: Learning to filter noisy labels with self-ensembling
DT Nguyen, CK Mummadi, TPN Ngo, THP Nguyen, L Beggel, T Brox
arXiv preprint arXiv:1910.01842, 2019
Adversarial examples for semantic image segmentation
V Fischer, MC Kumar, JH Metzen, T Brox
arXiv preprint arXiv:1703.01101, 2017
Deepusps: Deep robust unsupervised saliency prediction via self-supervision
T Nguyen, M Dax, CK Mummadi, N Ngo, THP Nguyen, Z Lou, T Brox
Advances in Neural Information Processing Systems 32, 2019
Real-time and embedded detection of hand gestures with an IMU-based glove
CK Mummadi, F Philips Peter Leo, K Deep Verma, S Kasireddy, ...
Informatics 5 (2), 28, 2018
Defending against universal perturbations with shared adversarial training
CK Mummadi, T Brox, JH Metzen
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
Test-time adaptation to distribution shift by confidence maximization and input transformation
CK Mummadi, R Hutmacher, K Rambach, E Levinkov, T Brox, JH Metzen
arXiv preprint arXiv:2106.14999, 2021
Real-time embedded recognition of sign language alphabet fingerspelling in an imu-based glove
CK Mummadi, FPP Leo, KD Verma, S Kasireddy, PM Scholl, ...
Proceedings of the 4th international Workshop on Sensor-based Activity …, 2017
Does enhanced shape bias improve neural network robustness to common corruptions?
CK Mummadi, R Subramaniam, R Hutmacher, J Vitay, V Fischer, ...
arXiv preprint arXiv:2104.09789, 2021
Method and device for improving the robustness against “adversarial examples”
CK Mummadi, JH Metzen, V Fischer
US Patent 11,055,632, 2021
Give me your attention: Dot-product attention considered harmful for adversarial patch robustness
G Lovisotto, N Finnie, M Munoz, CK Mummadi, JH Metzen
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
Diagvib-6: A diagnostic benchmark suite for vision models in the presence of shortcut and generalization opportunities
E Eulig, P Saranrittichai, CK Mummadi, K Rambach, W Beluch, X Shi, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
Group Pruning Using a Bounded- Norm for Group Gating and Regularization
CK Mummadi, T Genewein, D Zhang, T Brox, V Fischer
Pattern Recognition: 41st DAGM German Conference, DAGM GCPR 2019, Dortmund …, 2019
Overcoming Shortcut Learning in a Target Domain by Generalizing Basic Visual Factors from a Source Domain
P Saranrittichai, CK Mummadi, C Blaiotta, M Munoz, V Fischer
Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022
Multi-attribute Open Set Recognition
P Saranrittichai, CK Mummadi, C Blaiotta, M Munoz, V Fischer
Pattern Recognition: 44th DAGM German Conference, DAGM GCPR 2022, Konstanz …, 2022
Device and method for determining a semantic segmentation and/or an instance segmentation of an image
CK Mummadi, JH Metzen, R Hutmacher
US Patent App. 17/894,358, 2023
Image classifier with lesser requirement for labelled training data
P Saranrittichai, AMM Delgado, CK Mummadi, C Blaiotta, V Fischer
US Patent App. 17/861,440, 2023
Device and method to adapt a pretrained machine learning system to target data that has different distribution than the training data without the necessity of human annotations …
CK Mummadi, E Levinkov, JH Metzen, K Rambach, R Hutmacher
US Patent App. 17/747,361, 2022
Device and method for training a classifier using an invertible factorization model
V Fischer, CK Mummadi, T Pfeil
US Patent App. 17/448,110, 2022
Data-based updating of the training of classifier networks
CK Mummadi, JH Metzen, K Rambach, R Hutmacher
US Patent App. 17/479,161, 2022
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