1 code implementation • 20 Sep 2023 • Nastaran Darabi, Sina Tayebati, Sureshkumar S., Sathya Ravi, Theja Tulabandhula, Amit R. Trivedi
In diverse test scenarios involving adverse weather and sensor malfunctions, we show that STARNet enhances prediction accuracy by approximately 10% by filtering out untrustworthy sensor streams.
no code implementations • 18 Sep 2023 • Alex C. Stutts, Danilo Erricolo, Sathya Ravi, Theja Tulabandhula, Amit Ranjan Trivedi
In the expanding landscape of AI-enabled robotics, robust quantification of predictive uncertainties is of great importance.
no code implementations • 27 Oct 2022 • Priyesh Shukla, Sureshkumar S., Alex C. Stutts, Sathya Ravi, Theja Tulabandhula, Amit R. Trivedi
We present a novel monocular localization framework by jointly training deep learning-based depth prediction and Bayesian filtering-based pose reasoning.
no code implementations • 10 Jun 2015 • Vamsi K. Ithapu, Sathya Ravi, Vikas Singh
Unsupervised pretraining and dropout have been well studied, especially with respect to regularization and output consistency.
no code implementations • 12 Feb 2015 • Vamsi K. Ithapu, Sathya Ravi, Vikas Singh
The success of deep architectures is at least in part attributed to the layer-by-layer unsupervised pre-training that initializes the network.