An HMM Approach with Inherent Model Selection for Sign Language and Gesture Recognition

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

The human face plays an essential role in social interactions as it brings information about someone's identity, state of mind, or mood. People are, by nature, very good at catching this non-spoken information. Therefore, scientists have been interested in ...

Training deep neural networks (DNNs) can be difficult due to the occurrence of vanishing/explod- ing gradients during weight optimization. To avoid this problem, we propose a class of DNNs stemming from the time discretization of Hamiltonian systems. The t ...

We propose a deep neural network based image-to-image translation for domain adaptation, which aims at finding translations between image domains. Despite recent GAN based methods showing promising results in image-to-image translation, they are prone to f ...

Learning how to reach a reward over long series of actions is a remarkable capability of humans, and potentially guided by multiple parallel learning modules. Current brain imaging of learning modules is limited by (i) simple experimental paradigms, (ii) e ...

We introduce a method for automated grading of handwritten essays written by foreign language learners of French. The handwriting recognition system allows digitising the essays for further processing and functions at a low character error rate. The transc ...

The defective regimes in metal-based Laser Powder Bed Fusion (LPBF) processes can be minimized by deploying in-situ monitoring strategies comprising Machine learning (ML) algorithms and sensing techniques. So far, algorithms trained for monitoring a partic ...

Advances in soft sensors coupled with machine learning are enabling increasingly capable wearable systems. Since hand motion in particular can convey useful information for developing intuitive interfaces, glove-based systems can have a significant impact ...

A large body of research has focused on adversarial attacks which require to modify all input features with small l2- or l∞-norms. In this paper we instead focus on query-efficient sparse attacks in the black-box setting. Our versatile framework, Sparse-RS ...

State-of-the-art acoustic models for Automatic Speech Recognition (ASR) are based on Hidden Markov Models (HMM) and Deep Neural Networks (DNN) and often require thousands of hours of transcribed speech data during training. Therefore, building multilingual ...

Automatic Speech Recognition (ASR), as the assistance of speech communication between pilots and air-traffic controllers, can significantly reduce the complexity of the task and increase the reliability of transmitted information. ASR application can lead ...

Perceiving humans in the context of Intelligent Transportation Systems (ITS) often relies on multiple cameras or expensive LiDAR sensors. In this work, we present a new cost-effective vision-based method that perceives humans' locations in 3D and their bod ...

Cross-domain synthesizing realistic faces to learn deep models has attracted increasing attention for facial expression analysis as it helps to improve the performance of expression recognition accuracy despite having small number of real training images. ...

Aging civil infrastructures are closely monitored by engineers for damage and critical defects. As the manual inspection of such large structures is costly and time-consuming, we are working towards fully automating the visual inspections to support the pr ...

In this work, we present a simple biometric indexing scheme which is binning and retrieving cancelable deep face templates based on frequent binary patterns. The simplicity of the proposed approach makes it applicable to unprotected as well as protected, i ...

An HMM Approach with Inherent Model Selection for Sign Language and Gesture Recognition

Chattez avec Graph Search

Model-based 3D Face Reconstruction

A unified framework for Hamiltonian deep neural networks

ExprADA: Adversarial domain adaptation for facial expression analysis

Brain signals of a Surprise-Actor-Critic model: Evidence for multiple learning modules in human decision making

Automated Essay Scoring in Foreign Language Students Based on Deep Contextualised Word Representations

Deep transfer learning of additive manufacturing mechanisms across materials in metal-based laser powder bed fusion process

A Wearable Smart Glove and Its Application of Pose and Gesture Detection to Sign Language Classification

Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks

Multilingual Training and Adaptation in Speech Recognition

A Two-Step Approach To Leverage Contextual Data: Speech Recognition In Air-Traffic Communications

Perceiving Humans: from Monocular 3D Localization to Social Distancing

Using Photorealistic Face Synthesis and Domain Adaptation to Improve Facial Expression Analysis

Active Learning for Imbalanced Civil Infrastructure Data

Indexing Protected Deep Face Templates by Frequent Binary Patterns