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Publications associées (71)
Machine learning methods to assist energy system optimization
Jean-Louis Scartezzini, Amarasinghage Tharindu Dasun Perera, Vahid Moussavi Nik
This study evaluates the potential of supervised and transfer learning techniques to assist energy system optimization. A surrogate model is developed with the support of a supervised learning technique (by using artificial neural network) in order to bypa ...
2019Idiap submission to the NIST SRE 2019 Speaker Recognition Evaluation
Sébastien Marcel, Petr Motlicek
Idiap has made a submission to the conversational telephony speech (CTS) challenge of the NIST SRE 2019. The submission consists of six speaker verification (SV) systems: four extended TDNN (E-TDNN) and two TDNN x-vector systems. Employment of various trai ...
Idiap2019Fusing TensorFlow with building energy simulation for intelligent energy management in smart cities
Buildings account for 35% of the global final energy demand. Efficiency improvements and advanced control strategies have a significant impact in the reduction of energy costs and CO2 emissions. Building energy simulation is widely used to help planners, c ...
2019Muscle activities in similar arms performing identical tasks reveal the neural basis of muscle synergies
Are the muscle synergies extracted from multiple electromyographic signals an expression of neural information processing, or rather a by-product of mechanical and task constraints? To address this question, we asked 41 right-handed adults to perform a var ...
SPRINGER2019Multilingual Bottleneck Features For Query By Example Spoken Term Detection
State of the art solutions to query by example spoken term detection (QbE-STD) rely on bottleneck feature representation of the query and audio document. Here, we present a study on QbE-STD performance using several monolingual as well as multilingual bott ...
IEEE2019Domain Adaptation in Multi-Channel Autoencoder based Features for Robust Face Anti-Spoofing
While the performance of face recognition systems has improved significantly in the last decade, they are proved to be highly vulnerable to presentation attacks (spoofing). Most of the research in the field of face presentation attack detection (PAD), was ...
2019