Publications by Hesam Sagha | EPFL Graph Search

Stream fusion for multi-stream automatic speech recognition

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Hesam Sagha, Ehsan Variani

Multi-stream automatic speech recognition (MS-ASR) has been confirmed to boost the recognition performance in noisy conditions. In this system, the generation and the fusion of the streams are the essential parts and need to be designed in such a way to re ...

Springer Verlag2016

Quantifying electrode reliability during Brain-Computer Interface operation

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Serafeim Perdikis, Hesam Sagha

One of the problems of non-invasive Brain-Computer Interface (BCI) applications is the occurrence of anomalous (unexpected) signals that might degrade BCI performance. This situation might slip the operator’s attention since raw signals are not usually con ...

Institute of Electrical and Electronics Engineers2015

The Opportunity challenge: A benchmark database for on-body sensor-based activity recognition

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Hesam Sagha, Daniel Roggen

There is a growing interest on using ambient and wearable sensors for human activity recognition, fostered by several application domains and wider availability of sensing technologies. This has triggered increasing attention on the development of robust m ...

Elsevier2013

Robust Activity Recognition Combining Anomaly Detection and Classifier Retraining

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Hesam Sagha, Daniel Roggen

Activity recognition systems based on body-worn motion sensors suffer from a decrease in performance during the deployment and run-time phases, because of probable changes in the sensors (e.g. displacement or rotatation), which is the case in many real-lif ...

IEEE2013

Robust Activity Recognition Combining Anomaly Detection and Classifier Retraining

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Hesam Sagha, Daniel Roggen

Activity recognition systems based on body-worn motion sensors suffer from a decrease in performance during the deployment and run-time phases, because of probable changes in the sensors (e.g. displacement or rotation), which is the case in many real-life ...

2013

On-line anomaly detection and resilience in classifier ensembles

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Hesam Sagha, Hamidreza Bayati

Detection of anomalies is a broad field of study, which is applied in different areas such as data monitoring, navigation, and pattern recognition. In this paper we propose two measures to detect anomalous behaviors in an ensemble of classifiers by monitor ...

Elsevier2013

Dynamic Classifier Fusion for Multi-sensory Activity Recognition

Hesam Sagha

Nowadays, many systems rely on fusing different sources of information to recognize human activities and gestures, speech, or brain activities for applications in areas such as clinical practice, and health care and Human Computer Interaction (HCI). Typica ...

EPFL2013

Toward online detection of BCI performance degradation

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Serafeim Perdikis, Hesam Sagha

One of the problems of non-invasive BCI applications is the noise and change of EEG recordings that can result in performance degradation. Signal noise and changes can for instance be the result of electrode misplacements, impedances degradation or complet ...

2012

Kinect=IMU? Learning MIMO Signal Mappings to Automatically Translate Activity Recognition Systems Across Sensor Modalities

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Hesam Sagha, Daniel Roggen

We propose a method to automatically translate a pre-existing activity recognition system, devised for a source sensor domain S, so that it can operate on a newly discovered target sensor domain T , possibly of different modality. First, we use MIMO system ...

2012

The OPPORTUNITY Framework and Data Processing Ecosystem for Opportunistic Activity and Context Recognition

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Hesam Sagha, Daniel Roggen

Opportunistic sensing can be used to obtain data from sensors that just happen to be present in the user’s surroundings. By harnessing these opportunistic sensor configurations to infer activity or context, ambient intelligence environments become more rob ...

2012