13 citations · 24 across the 7 of their papers we have counts for
7 papers
Predictive Maneuver Planning with Deep Reinforcement Learning (PMP-DRL) for comfortable and safe autonomous driving
Jayabrata Chowdhury, Vishruth Veerendranath, Suresh Sundaram +1
This paper presents a Predictive Maneuver Planning with Deep Reinforcement Learning (PMP-DRL) model for maneuver planning. Traditional rule-based maneuver planning approaches often…
Fully Complex-valued Fully Convolutional Multi-feature Fusion Network (FC2MFN) for Building Segmentation of InSAR images
Aniruddh Sikdar, Sumanth Udupa, Suresh Sundaram +1
Building segmentation in high-resolution InSAR images is a challenging task that can be useful for large-scale surveillance. Although complex-valued deep learning networks perform…
Robust EMRAN-aided Coupled Controller for Autonomous Vehicles
Sauranil Debarshi, Suresh Sundaram, Narasimhan Sundararajan
This paper presents a coupled, neural network-aided longitudinal cruise and lateral path-tracking controller for an autonomous vehicle with model uncertainties and experiencing unk…
A Decentralized Multi-UAV Spatio-Temporal Multi-Task Allocation Approach for Perimeter Defense
Shridhar Velhal, Suresh Sundaram, Narasimhan Sundararajan
This paper provides a new solution approach to a multi-player perimeter defense game, in which the intruders' team tries to enter the territory, and a team of defenders protects th…
Gap Reduced Minimum Error Robust Simultaneous Estimation For Unstable Nano Air Vehicle
Jinraj V Pushpangathan, Harikumar Kandath, Suresh Sundaram +1
This paper proposes a novel Gap Reduced Minimum Error Robust Simultaneous (GRMERS) estimator for resource-constrained Nano Aerial Vehicle (NAV) that enables a single estimator to p…
Context-Aware Deep Q-Network for Decentralized Cooperative Reconnaissance by a Robotic Swarm
Nishant Mohanty, Mohitvishnu S. Gadde, Suresh Sundaram +2
One of the crucial problems in robotic swarm-based operation is to search and neutralize heterogeneous targets in an unknown and uncertain environment, without any communication wi…
A novel method for extracting interpretable knowledge from a spiking neural classifier with time-varying synaptic weights
Abeegithan Jeyasothy, Suresh Sundaram, Savitha Ramasamy +1
This paper presents a novel method for information interpretability in an MC-SEFRON classifier. To develop a method to extract knowledge stored in a trained classifier, first, the…