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pro vyhledávání: '"Rocamora, A"'
Autor:
Tapia, Juan E., Damer, Naser, Busch, Christoph, Espin, Juan M., Barrachina, Javier, Rocamora, Alvaro S., Ocvirk, Kristof, Alessio, Leon, Batagelj, Borut, Patwardhan, Sushrut, Ramachandra, Raghavendra, Mudgalgundurao, Raghavendra, Raja, Kiran, Schulz, Daniel, Aravena, Carlos
This paper summarises the Competition on Presentation Attack Detection on ID Cards (PAD-IDCard) held at the 2024 International Joint Conference on Biometrics (IJCB2024). The competition attracted a total of ten registered teams, both from academia an
Externí odkaz:
http://arxiv.org/abs/2409.00372
Publikováno v:
Sound and Music Computing Conference (SMC2024)
In the Western music tradition, chords are the main constituent components of harmony, a fundamental dimension of music. Despite its relevance for several Music Information Retrieval (MIR) tasks, chord-annotated audio datasets are limited and need mo
Externí odkaz:
http://arxiv.org/abs/2408.00674
Autoregressive generative transformers are key in music generation, producing coherent compositions but facing challenges in human-machine collaboration. We propose RefinPaint, an iterative technique that improves the sampling process. It does this b
Externí odkaz:
http://arxiv.org/abs/2407.09099
Adversarial attacks in Natural Language Processing apply perturbations in the character or token levels. Token-level attacks, gaining prominence for their use of gradient-based methods, are susceptible to altering sentence semantics, leading to inval
Externí odkaz:
http://arxiv.org/abs/2405.04346
Autor:
Ferrández, Antonio, Lavigne-Cerván, Rocío, Peral, Jesús, Navarro-Soria, Ignasi, Lloret, Ángel, Gil, David, Rocamora, Carmen
Publikováno v:
PeerJ Computer Science, Volume 10, February 2024, ID e1866
In this article, we present CuentosIE (TalesEI: chatbot of tales with a message to develop Emotional Intelligence), an educational chatbot on emotions that also provides teachers and psychologists with a tool to monitor their students/patients throug
Externí odkaz:
http://arxiv.org/abs/2403.07193
Autor:
Rocamora, Manuel, Ascasibar, Yago, Sánchez-Conde, Miguel A., Wechakama, Maneenate, Luque, Pedro de la Torre
We study the origin of the positron excess observed in the local cosmic-ray spectrum at high energies, and relate it to the cosmic rays and gamma-ray emission across the entire Galaxy. In particular, we explore the hypothesis of a single, dominant so
Externí odkaz:
http://arxiv.org/abs/2403.03303
Autor:
Alonso-Jiménez, Pablo, Pepino, Leonardo, Batlle-Roca, Roser, Zinemanas, Pablo, Bogdanov, Dmitry, Serra, Xavier, Rocamora, Martín
We present PECMAE, an interpretable model for music audio classification based on prototype learning. Our model is based on a previous method, APNet, which jointly learns an autoencoder and a prototypical network. Instead, we propose to decouple both
Externí odkaz:
http://arxiv.org/abs/2402.09318
Catastrophic overfitting (CO) in single-step adversarial training (AT) results in abrupt drops in the adversarial test accuracy (even down to 0%). For models trained with multi-step AT, it has been observed that the loss function behaves locally line
Externí odkaz:
http://arxiv.org/abs/2401.11618
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used approach for the generation of gene co-expression networks. However, networks generated with this tool usually create large modules with a large set of functional annotati
Externí odkaz:
https://doaj.org/article/737d3f96dbd24a19b21cf13ba6254261
Beat and downbeat tracking models have improved significantly in recent years with the introduction of deep learning methods. However, despite these improvements, several challenges remain. Particularly, the adaptation of available models to underrep
Externí odkaz:
http://arxiv.org/abs/2304.07186