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From the 1 of 6 linked papers with an AI index.

most citedEEG-based AI-BCI Wheelchair Advancement: Transformer-Based Learning with Motor Imagery for Brain Computer Interface

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

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6 papers

cs.LG20261 cited

EEG-based AI-BCI Wheelchair Advancement: Transformer-Based Learning with Motor Imagery for Brain Computer Interface

Bipul Thapa, Biplov Paneru, Bishwash Paneru +1

The paper proposes a Transformer‑based deep learning model (TFormerEEG) to classify motor‑imagery EEG signals for controlling a simulated wheelchair, achieving over 90% accuracy.

cs.LG2025

AI for Water Sustainability: Global Water Quality Assessment and Prediction with Explainable AI with LLM Chatbot for Insights

Biplov Paneru, Bishwash Paneru

Ensuring safe water supplies requires effective water quality monitoring, especially in developing countries like Nepal, where contamination risks are high. This paper introduces v…

cs.HC2025

EEG-based AI-BCI Wheelchair Advancement: A Brain-Computer Interfacing Wheelchair System Using Deep Learning Approach

Biplov Paneru, Bishwash Paneru, Bipul Thapa +1

This study offers a revolutionary strategy to developing wheelchairs based on the Brain-Computer Interface (BCI) that incorporates Artificial Intelligence (AI) using a The device u…

eess.SP2025

EEG Right & Left Voluntary Hand Movement-based Virtual Brain-Computer Interfacing Keyboard Using Hybrid Deep Learning Approach

Biplov Paneru, Bipul Thapa, Bishwash Paneru +1

Brain-machine interfaces (BMIs), particularly those based on electroencephalography (EEG), offer promising solutions for assisting individuals with motor disabilities. However, cha…

cs.LG2025

Remaining Useful Life Prediction for Batteries Utilizing an Explainable AI Approach with a Predictive Application for Decision-Making

Biplov Paneru, Bipul Thapa, Durga Prasad Mainali +2

Accurately estimating the Remaining Useful Life (RUL) of a battery is essential for determining its lifespan and recharge requirements. In this work, we develop machine learning-ba…

cs.LG2025

A review on development of eco-friendly filters in Nepal for use in cigarettes and masks and Air Pollution Analysis with Machine Learning and SHAP Interpretability

Bishwash Paneru, Biplov Paneru, Tanka Mukhiya +1

In Nepal, air pollution is a serious public health concern, especially in cities like Kathmandu where particulate matter (PM2.5 and PM10) has a major influence on respiratory healt…