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Cross-lingual transfer has been shown to increase the performance of a text classification model thanks to the use of Multilingual Hierarchical Attention Networks (MHAN), on which this work is based. Firstly, we compared the performance of monolingual and ...
Multi-session training conditions are becoming increasingly common in recent benchmark datasets for both text-independent and text-dependent speaker verification. In the state-of-the-art i-vector framework for speaker verification, such conditions are addr ...
A new method to automatically classify solid hydrometeors based on Multi-Angle Snowflake Camera (MASC) images is presented. For each individual image, the method relies on the calculation of a set of geometric and texture-based descriptors to simultaneousl ...
This paper aims to provide a road map for future works related to reverse engineering field of expertise. Reverse Engineering, in a mechanical context, relates to any process working in a bottom-up fashion, namely that it goes from a lower level concept or ...
We present the first prototype of the SUMMA Platform: an integrated platform for multilingual media monitoring. The platform contains a rich suite of low-level and high-level natural language processing technologies: automatic speech recognition of broadca ...
In the last decade, i-vector and Joint Factor Analysis (JFA) approaches to speaker modeling have become ubiquitous in the area of automatic speaker recognition. Both of these techniques involve the computation of posterior probabilities, using either Gauss ...
The work presented in this dissertation lies in the domains of image classification, object detection, and machine learning. Whether it is training image classifiers or object detectors, the learning phase consists in finding an optimal boundary between po ...
For many classification tasks, the ideal classifier should be invariant to geometric transformations such as changing the view angle. However, this cannot be said decisively for the state-of-the-art image classifiers, such as convolutional neural networks. ...
The work presented in this dissertation lies in the domains of image classification, object detection, and machine learning. Whether it is training image classifiers or object detectors, the learning phase consists in finding an optimal boundary between po ...
Nanoscale technology nodes bring reliability concerns back to the center stage of digital system design. A systematic classification of approaches that increase system resilience in the presence of functional hardware (HW)-induced errors is presented, deal ...
