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Arvind Kumar Shekar
Arvind Kumar Shekar
Data scientist, Bosch GmbH
Verified email at de.bosch.com - Homepage
Title
Cited by
Cited by
Year
VATLD: A Visual Analytics System to Assess, Understand and Improve Traffic Light Detection
L Gou, L Zou, N Li, M Hofmann, AK Shekar, A Wendt, L Ren
IEEE transactions on visualization and computer graphics 27 (2), 261-271, 2020
272020
Including multi-feature interactions and redundancy for feature ranking in mixed datasets
AK Shekar, T Bocklisch, PI Sánchez, CN Straehle, E Müller
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017
122017
Where Can We Help? A Visual Analytics Approach to Diagnosing and Improving Semantic Segmentation of Movable Objects
W He, L Zou, AK Shekar, L Gou, L Ren
IEEE Transactions on Visualization and Computer Graphics 28 (1), 1040-1050, 2021
102021
Label-Free Robustness Estimation of Object Detection CNNs for Autonomous Driving Applications
AK Shekar, L Gou, A Ren, Liu, Wendt
International Journal of Computer Vision, 2021
102021
Selection of relevant and non-redundant multivariate ordinal patterns for time series classification
AK Shekar, M Pappik, P Iglesias Sánchez, E Müller
Discovery Science: 21st International Conference, DS 2018, Limassol, Cyprus …, 2018
52018
Building robust prediction models for defective sensor data using artificial neural networks
CR de Sá, AK Shekar, H Ferreira, C Soares
14th International Conference on Soft Computing Models in Industrial and …, 2020
32020
Diverse selection of feature subsets for ensemble regression
AK Shekar, PI Sánchez, E Müller
Big Data Analytics and Knowledge Discovery: 19th International Conference …, 2017
32017
Visual Concept Programming: A Visual Analytics Approach to Injecting Human Intelligence at Scale
MN Hoque, W He, AK Shekar, L Gou, L Ren
IEEE Transactions on Visualization and Computer Graphics 29 (1), 74-83, 2022
22022
Self-supervised semantic segmentation grounded in visual concepts
W He, W Surmeier, AK Shekar, L Gou, L Ren
arXiv preprint arXiv:2203.13868, 2022
12022
Building robust prediction models for defective sensor data using Artificial Neural Networks
AK Shekar, CR de Sá, H Ferreira, C Soares
arXiv preprint arXiv:1804.05544, 2018
12018
Framework for exploring and understanding multivariate correlations
L Kirsch, N Riekenbrauck, D Thevessen, M Pappik, A Stebner, J Kunze, ...
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017
12017
Providing proactiveness: Data analysis techniques portfolios
A Sillitti, JF Anakabe, J Basurko, P Dam, H Ferreira, S Ferreiro, J Gijsbers, ...
The MANTIS Book, 145-238, 2022
2022
Novelty-based Generalization Evaluation for Traffic Light Detection
AK Shekar, L Lake, L Gou, L Ren
2021 20th IEEE International Conference on Machine Learning and Applications …, 2021
2021
Multivariate Correlation Analysis for Supervised Feature Selection in High-Dimensional Data
AK Shekar
Rheinische Friedrich-Wilhelms-Universität Bonn, 2020
2020
Building Robust Prediction Models for Defective Sensor Data Using Artificial Neural Networks
C Rebelo de Sá, AK Shekar, H Ferreira, C Soares
Springer, 2019
2019
The MANTIS book: Cyber physical system based proactive collaborative maintenance
A Sillitti, JF Anakabe, J Basurko, P Dam, H Ferreira, S Ferreiro, J Gijsbers, ...
The MANTIS Book: Cyber Physical System Based Proactive Collaborative Maintenance, 2018
2018
2020 IEEE Visualization Conference
L Gou, L Zou, N Li, M Hofmann, AK Shekar, A Wendt, L Ren
Selection of Relevant and Non-Redundant Multivariate Ordinal Patterns for Time Series Classification-Supplementary Material
AK Shekar, M Pappik, PI Sanchez, E Mueller
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