Search Results for author: Payal Kamboj

Found 6 papers, 0 papers with code

CPS-LLM: Large Language Model based Safe Usage Plan Generator for Human-in-the-Loop Human-in-the-Plant Cyber-Physical System

no code implementations19 May 2024 Ayan Banerjee, Aranyak Maity, Payal Kamboj, Sandeep K. S. Gupta

We explore the usage of large language models (LLM) in human-in-the-loop human-in-the-plant cyber-physical systems (CPS) to translate a high-level prompt into a personalized plan of actions, and subsequently convert that plan into a grounded inference of sequential decision-making automated by a real-world CPS controller to achieve a control goal.

Chatbot Language Modelling +1

The Expert Knowledge combined with AI outperforms AI Alone in Seizure Onset Zone Localization using resting state fMRI

no code implementations14 Dec 2023 Payal Kamboj, Ayan Banerjee, Varina L. Boerwinkle, Sandeep K. S. Gupta

We evaluated whether integration of expert guidance on seizure onset zone (SOZ) identification from resting state functional MRI (rs-fMRI) connectomics combined with deep learning (DL) techniques enhances the SOZ delineation in patients with refractory epilepsy (RE), compared to utilizing DL alone.

EEG

High Fidelity Fast Simulation of Human in the Loop Human in the Plant (HIL-HIP) Systems

no code implementations10 Sep 2023 Ayan Banerjee, Payal Kamboj, Aranyak Maity, Riya Sudhakar Salian, Sandeep K. S. Gupta

Non-linearities in simulation arise from the time variance in wireless mobile networks when integrated with human in the loop, human in the plant (HIL-HIP) physical systems under dynamic contexts, leading to simulation slowdown.

Transfer: Cross Modality Knowledge Transfer using Adversarial Networks -- A Study on Gesture Recognition

no code implementations26 Jun 2023 Payal Kamboj, Ayan Banerjee, Sandeep K. S. Gupta

Knowledge transfer across sensing technology is a novel concept that has been recently explored in many application domains, including gesture-based human computer interaction.

Gesture Recognition Transfer Learning

EdGCon: Auto-assigner of Iconicity Ratings Grounded by Lexical Properties to Aid in Generation of Technical Gestures

no code implementations2 Jun 2023 Sameena Hossain, Payal Kamboj, Aranyak Maity, Tamiko Azuma, Ayan Banerjee, Sandeep K. S. Gupta

EdGCon assigned an iconicity rating based on the lexical property similarities of the new gesture with an existing set of technical gestures and the relatedness of the meaning of the new technical word to that of the existing set of technical words.

Cannot find the paper you are looking for? You can Submit a new open access paper.