Publications associées à Boosting of contextual information in ASR for air-traffic call-sign recognition

Social-Transmotion: Promptable Human Trajectory Prediction

Alexandre Massoud Alahi, Saeed Saadatnejad, Yang Gao, Kaouther Messaoud Ben Amor

Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage the non-verbal social cues human subconsciously communicate when navigating ...

2024

A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers

Petr Motlicek, Amrutha Prasad, Juan Pablo Zuluaga Gomez

In this paper we propose a novel virtual simulation-pilot engine for speeding up air traffic controller (ATCo) training by integrating different state-of-the-art artificial intelligence (AI)-based tools. The virtual simulation-pilot engine receives spoken ...

MDPI2023

How to Boost Face Recognition with StyleGAN?

Nikita Durasov

State-of-the-art face recognition systems require vast amounts of labeled training data. Given the priority of privacy in face recognition applications, the data is limited to celebrity web crawls, which have issues such as limited numbers of identities. O ...

Ieee Computer Soc2023

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

Petr Motlicek, Amrutha Prasad, Juan Pablo Zuluaga Gomez

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 ...

IEEE2022

Indexing Protected Deep Face Templates by Frequent Binary Patterns

Sébastien Marcel, Hatef Otroshi Shahreza

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 ...

IEEE2022

Automatic Call Sign Detection: Matching Air Surveillance Data with Air Traffic Spoken Communications

Petr Motlicek, Amrutha Prasad

Voice communication is the main channel to exchange information between pilots and Air-Traffic Controllers (ATCos). Recently, several projects have explored the employment of speech recognition technology to automatically extract spoken key information suc ...

MDPI2021

On the Recognition Performance of BioHashing on state-of-the-art Face Recognition models

Sébastien Marcel, Hatef Otroshi Shahreza

Face recognition has become a popular authentication tool in recent years. Modern state-of-the-art (SOTA) face recognition methods rely on deep neural networks, which extract discriminative features from face images. Although these methods have high recogn ...

IEEE2021

Flying in Private Mode: Understanding and Improving the Privacy ICAO Address Program

Guillaume Michel Le Bars

Location privacy of aircraft has recently gained attention as air traffic management was modernized using novel surveillance technologies. Business aviation circles and various military and government entities voiced serious concerns about automated and ub ...

AMER INST AERONAUTICS ASTRONAUTICS2021

ExprADA: Adversarial domain adaptation for facial expression analysis

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar

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 ...

2020

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

Jean-Philippe Thiran, Mohammad Saeed Rad, Hazim Kemal Ekenel

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. ...

IEEE2019

Multimodal person recognition in audio-visual streams

Do Hoang Nam Le

Multimedia databases are growing rapidly in size in the digital age. To increase the value of these data and to enhance the user experience, there is a need to make these videos searchable through automatic indexing. Because people appearing and talking in ...

EPFL2019

Detection of Age-Induced Makeup Attacks on Face Recognition Systems Using Multi-Layer Deep Features

Sébastien Marcel, Zohreh Mostaani

Makeup is a simple and easy instrument that can alter the appearance of a person’s face, and hence, create a presentation attack on face recognition (FR) systems. These attacks, especially the ones mimicking ageing, are difficult to detect due to their clo ...

2020

Precision Global Health - The case of Ebola: a scoping review

Gérard Escher

Background The 2014-2016 Ebola outbreak across West Africa was devastating, acting not only as a wake-up call for the global health community, but also as a catalyst for innovative change and global action. Improved infectious disease monitoring is the ste ...

2019

UAV-Based Situational Awareness System Using Deep Learning

Wenlong Deng

Situational awareness by Unmanned Aerial Vehicles (UAVs) is important for many applications such as surveillance, search and rescue, and disaster response. In those applications, detecting and locating people and recognizing their actions in near real-time ...

2019

Behavioural compass: animal behaviour recognition using magnetometers

Kamiar Aminian, Pritish Chakravarty, Maiki Maalberg

Animal-borne data loggers today often house several sensors recording simultaneously at high frequency. This offers opportunities to gain fine-scale insights into behaviour from individual-sensor as well as integrated multi-sensor data. In the context of b ...

2019

Embedding Local Quality Measures in Minutiae-Based Biometric Recognition

Mohammad Hamed Izadi

Degradation in data quality is still a main source of errors in the modern biometric recognition systems. However, the data quality can be embedded in the recognition methods at global and local levels to build more accurate biometric systems. Local qualit ...

EPFL2016

Food/Non-food Image Classification and Food Categorization using Pre-Trained GoogLeNet Model

Touradj Ebrahimi, Lin Yuan, Ashutosh Singla

Recent past has seen a lot of developments in the field of image-based dietary assessment. Food image classification and recognition are crucial steps for dietary assessment. In the last couple of years, advancements in the deep learning and convolutional ...

Assoc Computing Machinery2016

Towards End-to-End Speech Recognition

Dimitri Palaz

Standard automatic speech recognition (ASR) systems follow a divide and conquer approach to convert speech into text. Alternately, the end goal is achieved by a combination of sub-tasks, namely, feature extraction, acoustic modeling and sequence decoding, ...

EPFL2016

Visual Speech Recognition Using PCA Networks and LSTMs in a Tandem GMM-HMM System

Jean-Philippe Thiran, Marina Zimmermann, Mostafa Mehdipour Ghazi

Automatic visual speech recognition is an interesting problem in pattern recognition especially when audio data is noisy or not readily available. It is also a very challenging task mainly because of the lower amount of information in the visual articulati ...

Springer International Publishing2016

Impact of Mini-drone based Video Surveillance on Invasion of Privacy

Touradj Ebrahimi, Margherita Bonetto

An increase in adoption of video surveillance, affecting many aspects of daily lives, raises public concern about an intrusion into individual privacy. New sensing and surveillance technologies, such as mini-drones, threaten to eradicate boundaries of priv ...

2015