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pro vyhledávání: '"Pascu, Octavian"'
In this paper, we demonstrate that attacks in the latest ASVspoof5 dataset -- a de facto standard in the field of voice authenticity and deepfake detection -- can be identified with surprising accuracy using a small subset of very simplistic features
Externí odkaz:
http://arxiv.org/abs/2408.15775
Towards generalisable and calibrated synthetic speech detection with self-supervised representations
Generalisation -- the ability of a model to perform well on unseen data -- is crucial for building reliable deepfake detectors. However, recent studies have shown that the current audio deepfake models fall short of this desideratum. In this work we
Externí odkaz:
http://arxiv.org/abs/2309.05384
Autor:
Visan, Catalin, Pascu, Octavian, Stanescu, Marius, Sandru, Elena-Diana, Diaconu, Cristian, Buzo, Andi, Pelz, Georg, Cucu, Horia
With the ever increasing complexity of specifications, manual sizing for analog circuits recently became very challenging. Especially for innovative, large-scale circuits designs, with tens of design variables, operating conditions and conflicting ob
Externí odkaz:
http://arxiv.org/abs/2206.02391
Autor:
Oneata, Dan, Alexandru, Cosmin George, Stanescu, Marius, Pascu, Octavian, Magan, Alexandru, Postelnicu, Adrian, Cucu, Horia
We describe the submission of the Quo Vadis team to the Traffic4cast competition, which was organized as part of the NeurIPS 2019 series of challenges. Our system consists of a temporal regression module, implemented as $1\times1$ 2d convolutions, au
Externí odkaz:
http://arxiv.org/abs/1910.12363