NeuroAiR: Deep Learning Framework for Airwriting Recognition from Scalp-recorded Neural Signals
Airwriting recognition is a task that involves identifying letters written in free space using
finger movement. It is a special case of gesture recognition, where gestures correspond to …
finger movement. It is a special case of gesture recognition, where gestures correspond to …
SurfMyoAiR: A surface electromyography-based framework for airwriting recognition
Airwriting recognition is the task of identifying letters written in free space with finger
movement. It is a dynamic gesture recognition with the vocabulary of gestures …
movement. It is a dynamic gesture recognition with the vocabulary of gestures …
TripCEAiR: A multi-loss minimization approach for surface EMG based airwriting recognition
Airwriting Recognition refers to the problem of identification of letters written in space with
movement of the finger. It can be seen as a special case of dynamic gesture recognition …
movement of the finger. It can be seen as a special case of dynamic gesture recognition …
In-air handwriting system based on multi-scale channel attention network and monocular vision
X Qu, M Ye, W Zhao - Applied Soft Computing, 2024 - Elsevier
In-air handwriting based on a monocular camera is an innovative and promising modality for
human–computer interaction, offering a plethora of potential applications. However, existing …
human–computer interaction, offering a plethora of potential applications. However, existing …
Letter and Person Recognition in Freeform Air-Writing using Machine Learning Algorithms
H Kunt, Z Yetgin, F Gozukara, T Celik - IEEE Access, 2025 - ieeexplore.ieee.org
Air-writing is an emerging form of human-computer interaction that enables text entry
through hand movements in the air. This paper explores air-writing-based person …
through hand movements in the air. This paper explores air-writing-based person …
Continuous Hand Gestures Detection and Recognition in Emergency Human-Robot Interaction Based on the Inertial Measurement Unit
S Wang, T Zhang, Y Li, P Li, H Wu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Robots have become increasingly prevalent in various aspects of daily life. In an increasing
number of scenarios, particularly in social contexts, such as those involving delivery robots …
number of scenarios, particularly in social contexts, such as those involving delivery robots …
Deep Learning-based Classification of Dementia using Image Representation of Subcortical Signals
Dementia is a neurological syndrome marked by cognitive decline. Alzheimer's disease
(AD) and Frontotemporal dementia (FTD) are the common forms of dementia, each with …
(AD) and Frontotemporal dementia (FTD) are the common forms of dementia, each with …
Prism: Mining Task-aware Domains in Non-iid IMU Data for Flexible User Perception
A wide range of user perception applications leverage inertial measurement unit (IMU) data
for online prediction. However, restricted by the non-iid nature of IMU data collected from …
for online prediction. However, restricted by the non-iid nature of IMU data collected from …
Gesture Recognition Methods Using Sensors Integrated into Smartwatches: Results of a Systematic Literature Review
PRI Gomes, MS Castro, TH Nascimento - Proceedings of the XXII …, 2023 - dl.acm.org
This work addresses the importance of gesture recognition in smartwatches and aims to
conduct a systematic literature review to identify the most commonly used methods and …
conduct a systematic literature review to identify the most commonly used methods and …
Identification of Gas-Solid Two-Phase Flow Regimes Based on Electrostatic Sensor and CB-ResNext Network
J Lu, H Hu, H Cai, H Yang, H Zhang… - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Electrostatic sensors are commonly used to extract parameter information from gas-solid two-
phase flow in the energy and power industry, characterized by a simple structure and high …
phase flow in the energy and power industry, characterized by a simple structure and high …