Real-time hand gesture recognition based on deep learning YOLOv3 model
Using gestures can help people with certain disabilities in communicating with other people.
This paper proposes a lightweight model based on YOLO (You Only Look Once) v3 and …
This paper proposes a lightweight model based on YOLO (You Only Look Once) v3 and …
[HTML][HTML] Continuous word level sign language recognition using an expert system based on machine learning
R Sreemathy, MP Turuk, S Chaudhary, K Lavate… - International Journal of …, 2023 - Elsevier
The study of sign language recognition systems has been extensively explored using many
image processing and artificial intelligence techniques for many years, but the main …
image processing and artificial intelligence techniques for many years, but the main …
On efficient real-time semantic segmentation: a survey
CJ Holder, M Shafique - arxiv preprint arxiv:2206.08605, 2022 - arxiv.org
Semantic segmentation is the problem of assigning a class label to every pixel in an image,
and is an important component of an autonomous vehicle vision stack for facilitating scene …
and is an important component of an autonomous vehicle vision stack for facilitating scene …
An intelligent heuristic manta-ray foraging optimization and adaptive extreme learning machine for hand gesture image recognition
S Khetavath, NC Sendhilkumar… - Big Data Mining and …, 2023 - ieeexplore.ieee.org
The development of hand gesture recognition systems has gained more attention in recent
days, due to its support of modern human-computer interfaces. Moreover, sign language …
days, due to its support of modern human-computer interfaces. Moreover, sign language …
TMMF: Temporal multi-modal fusion for single-stage continuous gesture recognition
Gesture recognition is a much studied research area which has myriad real-world
applications including robotics and human-machine interaction. Current gesture recognition …
applications including robotics and human-machine interaction. Current gesture recognition …
Domain adaptive hand keypoint and pixel localization in the wild
We aim to improve the performance of regressing hand keypoints and segmenting pixel-
level hand masks under new imaging conditions (eg., outdoors) when we only have labeled …
level hand masks under new imaging conditions (eg., outdoors) when we only have labeled …
Real-time automated detection of older adults' hand gestures in home and clinical settings
There is an urgent need, accelerated by the COVID-19 pandemic, for methods that allow
clinicians and neuroscientists to remotely evaluate hand movements. This would help detect …
clinicians and neuroscientists to remotely evaluate hand movements. This would help detect …
Optimal video processing and soft computing algorithms for human hand gesture recognition from real-time video
An essential component of building an automated hand gesture detection system is the
ability to extract hand movements using a single video camera. Results for hand extraction …
ability to extract hand movements using a single video camera. Results for hand extraction …
[HTML][HTML] Efficient gesture recognition for the assistance of visually impaired people using multi-head neural networks
Existing research for the assistance of visually impaired people mainly focus on solving a
single task (such as reading a text or detecting an obstacle), hence forcing the user to switch …
single task (such as reading a text or detecting an obstacle), hence forcing the user to switch …
No interface, no problem: gesture recognition on physical objects using radar sensing
Physical objects are usually not designed with interaction capabilities to control digital
content. Nevertheless, they provide an untapped source for interactions since every object …
content. Nevertheless, they provide an untapped source for interactions since every object …