Quantitative survey of the state of the art in sign language recognition
O Koller - arXiv preprint arXiv:2008.09918, 2020 - arxiv.org
This work presents a meta study covering around 300 published sign language recognition
papers with over 400 experimental results. It includes most papers between the start of the …
papers with over 400 experimental results. It includes most papers between the start of the …
COVID-19 prediction and detection using deep learning
Currently, the detection of coronavirus disease 2019 (COVID-19) is one of the main
challenges in the world, given the rapid spread of the disease. Recent statistics indicate that …
challenges in the world, given the rapid spread of the disease. Recent statistics indicate that …
Revisiting data augmentation for rotational invariance in convolutional neural networks
Abstract Convolutional Neural Networks (CNN) offer state of the art performance in various
computer vision tasks. Many of those tasks require different subtypes of affine invariances …
computer vision tasks. Many of those tasks require different subtypes of affine invariances …
Alabib-65: A realistic dataset for algerian sign language recognition
K Khellas, R Seghir - ACM Transactions on Asian and Low-Resource …, 2023 - dl.acm.org
Sign language recognition (SLR) is a promising research field that aims to blur boundaries
between Deaf and hearing people by creating a system that can transcribe signs into a …
between Deaf and hearing people by creating a system that can transcribe signs into a …
A comparison of small sample methods for handshape recognition
F Ronchetti, F Quiroga, UJC Fandos… - Journal of …, 2023 - journal.info.unlp.edu.ar
Abstract Automatic Sign Language Translation (SLT) systems can be a great asset to
improve the communication with and within deaf communities. Currently, the main issue …
improve the communication with and within deaf communities. Currently, the main issue …
Transfer: Cross Modality Knowledge Transfer using Adversarial Networks--A Study on Gesture Recognition
Knowledge transfer across sensing technology is a novel concept that has been recently
explored in many application domains, including gesture-based human computer …
explored in many application domains, including gesture-based human computer …
Handshape recognition using principal component analysis and convolutional neural networks applied to sign language
M Oliveira - 2018 - doras.dcu.ie
Handshape recognition is an important problem in computer vision with significant societal
impact. However, it is not an easy task, since hands are naturally deformable objects …
impact. However, it is not an easy task, since hands are naturally deformable objects …
Recognizing handshapes using small datasets
UJ Cornejo Fandos, GG Rios, F Ronchetti… - … de Ciencias de la …, 2019 - sedici.unlp.edu.ar
Advances in convolutional neural networks have made possible significant improvements in
the state-of-the-art in image classification. However, their success on a particular field rests …
the state-of-the-art in image classification. However, their success on a particular field rests …
[PDF][PDF] Covid-19 Prediction And Detection Using Convolution Neural Networks
RK Duggirala - Webology (ISSN: 1735-188X), 2021 - webology.org
Currently, the detection of coronavirus disease 2019 (COVID-19) is one of the main
challenges in the world, given the rapid spread of the disease. Recent statistics indicate that …
challenges in the world, given the rapid spread of the disease. Recent statistics indicate that …
Resumen de tesis: Medidas de invarianza y equivarianza a transformaciones en redes neuronales convolucionales. Aplicaciones al reconocimiento de formas de …
FM Quiroga - XXII Workshop de Investigadores en Ciencias de la …, 2020 - sedici.unlp.edu.ar
Nuestro objetivo general en esta tesis es contribuir al entendimiento y mejora de la
equivarianza de los modelos de redes neuronales, en particular aplicados a la clasificación …
equivarianza de los modelos de redes neuronales, en particular aplicados a la clasificación …