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Found 9 papers, 2 papers with code
First Experiences with the Identification of People at Risk for Diabetes in Argentina using Machine Learning Techniques
In this article, the development and assessment of predictive models to identify people at risk for T2D and PD specifically in Argentina are discussed.
LSA64: An Argentinian Sign Language Dataset
The dataset, called LSA64, contains 3200 videos of 64 different LSA signs recorded by 10 subjects, and is a first step towards building a comprehensive research-level dataset of Argentinian signs, specifically tailored to sign language recognition or other machine learning tasks.
Handshape recognition for Argentinian Sign Language using ProbSom
Automatic sign language recognition is an important topic within the areas of human-computer interaction and machine learning.
Ranked #3 on
Hand Gesture Recognition
on LSA16
Distribution of Action Movements (DAM): A Descriptor for Human Action Recognition
Human action recognition from skeletal data is an important and active area of research in which the state of the art has not yet achieved near-perfect accuracy on many well-known datasets.
Ranked #1 on
Skeleton Based Action Recognition
on MSR Action3D
Sign Languague Recognition without frame-sequencing constraints: A proof of concept on the Argentinian Sign Language
The model employs a bag-of-words approach in all classification steps, to explore the hypothesis that ordering is not essential for recognition.
Revisiting Data Augmentation for Rotational Invariance in Convolutional Neural Networks
In the case of data augmented networks, we also analyze which layers help the network to encode the rotational invariance, which is important for understanding its limitations and how to best retrain a network with data augmentation to achieve invariance to rotation.
A comparison of small sample methods for Handshape Recognition
We compare a series of models specially tailored for small datasets to improve their performance on handshape recognition tasks.
LSA-T: The first continuous Argentinian Sign Language dataset for Sign Language Translation
Sign language translation (SLT) is an active field of study that encompasses human-computer interaction, computer vision, natural language processing and machine learning.
Ranked #1 on
Sign Language Translation
on LSA-T
Sign Language Recognition Without Frame-Sequencing Constraints: A Proof of Concept on the Argentinian Sign Language
The model employs a bag-of-words approach in all classification steps, to explore the hypothesis that ordering is not essential for recognition.
Ranked #2 on
Sign Language Recognition
on LSA64
