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Innovative hand pose based sign language recognition using hybrid metaheuristic optimization algorithms with deep learning model for hearing impaired persons. [PDF]

Sci Rep
Alabduallah B, Al Dayil R, Al Dayil R, Alkharashi A, Alneil AA.   +4 more
europepmc   +1 more source

Real-Time Arabic Sign Language Recognition Using a Hybrid Deep Learning Model. [PDF]

Sensors (Basel)
Noor TH, Noor A, Alharbi AF, Faisal A, Alrashidi R, Alsaedi AS, Alharbi G, Alsanoosy T, Alsaeedi A.   +8 more
europepmc   +1 more source

Retraction Note: Sign language recognition using the fusion of image and hand landmarks through multi-headed convolutional neural network. [PDF]

Sci Rep
Pathan RK, Biswas M, Yasmin S, Khandaker MU, Salman M, Youssef AAF.   +5 more
europepmc   +1 more source

LAVRF: Sign language recognition via Lightweight Attentive VGG16 with Random Forest. [PDF]

PLoS One
Ewe ELR, Lee CP, Lim KM, Kwek LC, Alqahtani A.   +4 more
europepmc   +1 more source

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Sign language recognition

2007 9th International Symposium on Signal Processing and Its Applications, 2007
In this paper, an image processing algorithm is presented for the interpretation of the Taiwanese sign language, which is one of the sign languages used by the majority of the deaf community. The process involves two layer classifications. At first, coarse classification is done according to detection of hand motion and tracking the hand location and ...
Maryam Pahlevanzadeh, Mansour Vafadoost, Majid Shahnazi   +2 more
openaire   +1 more source

Sign language recognition

2016 3rd International Conference on Recent Advances in Information Technology (RAIT), 2016
This paper presents a novel system to aid in communicating with those having vocal and hearing disabilities. It discusses an improved method for sign language recognition and conversion of speech to signs. The algorithm devised is capable of extracting signs from video sequences under minimally cluttered and dynamic background using skin color ...
Anup Kumar, Karun Thankachan, Mevin M. Dominic   +2 more
openaire   +1 more source

Australian sign language recognition

Machine Vision and Applications, 2005
This paper presents an automatic Australian sign language (Auslan) recognition system, which tracks multiple target objects (the face and hands) throughout an image sequence and extracts features for the recognition of sign phrases. Tracking is performed using correspondences of simple geometrical features between the target objects within the current ...
Eun-Jung Holden, Gareth Lee, Robyn A. Owens   +2 more
openaire   +1 more source

A Survey on Sign Language Recognition

2011 Frontiers of Information Technology, 2011
Sign Language (SL) recognition is getting more and more attention of the researchers due to its widespread applicability in many fields. This paper is based on the survey of the current research trends in the field of SL recognition to highlight the current status of different research aspects of the area.
Sumaira Kausar, Muhammad Younus Javed
openaire   +1 more source

Visual Sign Language Recognition

2001
Automatic gesture recognition systems generally require two separate processes: a motion sensing process where some motion features are extracted from the visual input; and a classification process where the features are recognised as gestures. We have developed the Hand Motion Understanding (HMU) system that uses the combination of a 3D model-based ...
Eun-Jung Holden, Robyn A. Owens
openaire   +1 more source

Static and Dynamic Isolated Indian and Russian Sign Language Recognition with Spatial and Temporal Feature Detection Using Hybrid Neural Network

ACM Transactions on Asian and Low-Resource Language Information Processing, 2023
E Rajalakshmi, R Elakkiya, Alexey L Prikhodko   +2 more
exaly