6 citations · 12 across the 3 of their papers we have counts for
4 papers
A Deep 2-Dimensional Dynamical Spiking Neuronal Network for Temporal Encoding trained with STDP
Matthew Evanusa, Cornelia Fermuller, Yiannis Aloimonos
The brain is known to be a highly complex, asynchronous dynamical system that is highly tailored to encode temporal information. However, recent deep learning approaches to not tak…
PRGFlow: Benchmarking SWAP-Aware Unified Deep Visual Inertial Odometry
Nitin J. Sanket, Chahat Deep Singh, Cornelia Fermüller +1
Odometry on aerial robots has to be of low latency and high robustness whilst also respecting the Size, Weight, Area and Power (SWAP) constraints as demanded by the size of the rob…
Following Instructions by Imagining and Reaching Visual Goals
John Kanu, Eadom Dessalene, Xiaomin Lin +2
While traditional methods for instruction-following typically assume prior linguistic and perceptual knowledge, many recent works in reinforcement learning (RL) have proposed learn…
EVDodgeNet: Deep Dynamic Obstacle Dodging with Event Cameras
Nitin J. Sanket, Chethan M. Parameshwara, Chahat Deep Singh +4
Dynamic obstacle avoidance on quadrotors requires low latency. A class of sensors that are particularly suitable for such scenarios are event cameras. In this paper, we present a d…