activity
20232025
most citedUnlocking Real-Time Fluorescence Lifetime Imaging: Multi-Pixel Parallelism for FPGA-Accelerated Processing

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

EvidenceMoE: A Physics-Guided Mixture-of-Experts with Evidential Critics for Advancing Fluorescence Light Detection and Ranging in Scattering Media

Ismail Erbas, Ferhat Demirkiran, Karthik Swaminathan +6

Fluorescence LiDAR (FLiDAR), a Light Detection and Ranging (LiDAR) technology employed for distance and depth estimation across medical, automotive, and other fields, encounters si…

physics.optics20241 cited

Unlocking Real-Time Fluorescence Lifetime Imaging: Multi-Pixel Parallelism for FPGA-Accelerated Processing

Ismail Erbas, Aporva Amarnath, Vikas Pandey +3

Fluorescence lifetime imaging (FLI) is a widely used technique in the biomedical field for measuring the decay times of fluorescent molecules, providing insights into metabolic sta…

cs.AR2024

Towards Generalized On-Chip Communication for Programmable Accelerators in Heterogeneous Architectures

Joseph Zuckerman, John-David Wellman, Ajay Vanamali +8

We present several enhancements to the open-source ESP platform to support flexible and efficient on-chip communication for programmable accelerators in heterogeneous SoCs. These e…

cs.RO2024

Anticipate & Collab: Data-driven Task Anticipation and Knowledge-driven Planning for Human-robot Collaboration

Shivam Singh, Karthik Swaminathan, Raghav Arora +6

An agent assisting humans in daily living activities can collaborate more effectively by anticipating upcoming tasks. Data-driven methods represent the state of the art in task ant…

cs.RO2023

BERRY: Bit Error Robustness for Energy-Efficient Reinforcement Learning-Based Autonomous Systems

Zishen Wan, Nandhini Chandramoorthy, Karthik Swaminathan +3

Autonomous systems, such as Unmanned Aerial Vehicles (UAVs), are expected to run complex reinforcement learning (RL) models to execute fully autonomous position-navigation-time tas…