Sign language recognition using the fusion of image and hand ...

This study demonstrates a cost-effective technique to detect American Sign Language (ASL) using an image dataset.

Abstract Sign Language Recognition is a breakthrough for communication among deaf-mute society and has been a critical research topic for years.

Sign language recognition using the fusion of image and hand ...

PubMed journal article: Sign language recognition using the fusion of image and hand landmarks through multi-headed convolutional neural network.

Sign language recognition using the fusion of image and hand ...

Sign language recognition using the fusion of image and hand landmarks through multi-headed convolutional neural network · Refat Khan Pathan · Munmun Biswas ...

Sign Language Recognition Using Hand Gesture from Image

PDF | Hand gesture recognition plays a key role in human-robot interaction, particularly in contexts such as American Sign Language (ASL) ...

Sign language recognition based on dual-path background erasure ...

Sign language recognition using the fusion of image and hand landmarks through multi-headed convolutional neural network. Sci. Rep. 13(1) ...

Dynamic Hand Gesture Based Sign Word Recognition Using ...

Gesture-based sign language recognition systems play an important role in human-computer interaction to develop communication between deaf communities and ...

[PDF] Multi-Modal Deep Hand Sign Language Recognition in Still ...

Multi-Modal Deep Hand Sign Language Recognition in Still Images Using Restricted Boltzmann Machine · Figures and Tables · Topics · 79 Citations · 28 References ...

Hand Gesture Recognition using Image Processing and Feature ...

Standard American Sign Language (ASL) images of a person's hand photographed under several different environmental conditions are taken as the dataset. The main ...

Sign Language Recognition Using Graph and General Deep Neural ...

Existing efforts in automatic sign recognition predominantly rely on hand skeleton joint information, steering clear of image pixels to address ...

sign-language-recognition-system · GitHub Topics

... with normal people using hand gesture to speech conversion. In this code we ... sign-language image-processing kinect image-recognition convex-hull hand ...

Sign Language Recognition with Multimodal Sensors and Deep ...

It estimates the complete 3D hand shape and poses from a monocular RGB image. Multimodal sensor data fusion methods are crucial in systems that combine bending ...

Static hand gesture recognition in sign language based on ...

In the proposed structure, the hand gesture image, after preprocessing and removing its background, passes through three different streams of feature extraction ...

Sign Language Recognition Application Systems for Deaf-Mute ...

... sign language hand gestures, with ... Sign language recognition using the fusion of image and hand landmarks through multi-headed convolutional neural network.

Multi-View Fusion for Sign Language Recognition through ...

Existing WSLR methods focus on recognizing frontal view hand images, which may hurt performance due to hand occlusion. However, non-frontal view ...

Deep learning-based sign language recognition system using both ...

Deep learning-based sign language recognition system using both manual and non-manual components fusion. Maher Jebali , ,; Abdesselem Dakhli , ...

Hand Sign Recognition using CNN

... Sign language recognition with multi feature fusion and ANN classifier ... and Lokesh B. Image enhancement with contrast coefficients using wavelet based image ...

Multi-Modal Deep Hand Sign Language Recognition in Still Images ...

They achieved the highest accuracy results of the challenge, using early fusion of joint motion features from two input modalities [12].

British Sign Language Recognition via Late Fusion of Computer ...

... hand through stereoscopy similar to human depth perception via images from two eyeballs. ... hand gesture recognition towards sign language ...

Hand-Model-Aware Sign Language Recognition

To this end, we use the results based on hand modeling, full keypoints and full RGB data. Those results can be assembled with late fusion by directly sum- ming ...