From the 1 of 6 linked papers with an AI index.
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6 papers
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.
A systematic review of assistive technologies for children with dyslexia
Sansrit Paudel, Subek Acharya, Piriyankan Kirupaharan +2
Dyslexia is a neurological learning disability that primarily disrupts one's ability to read, write, and spell, affecting an estimated 15-20% of the global population. This high pr…
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…
Emotion Classification In-Context in Spanish
Bipul Thapa, Gabriel Cofre
Classifying customer feedback into distinct emotion categories is essential for understanding sentiment and improving customer experience. In this paper, we classify customer feedb…
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…
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…