Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Kiskin, Ivan"'
Autor:
Nolasco, Ines, Ghani, Burooj, Singh, Shubhr, Vidaña-Vila, Ester, Whitehead, Helen, Grout, Emily, Emmerson, Michael, Jensen, Frants, Kiskin, Ivan, Morford, Joe, Strandburg-Peshkin, Ariana, Gill, Lisa, Pamuła, Hanna, Lostanlen, Vincent, Stowell, Dan
Few-shot bioacoustic event detection consists in detecting sound events of specified types, in varying soundscapes, while having access to only a few examples of the class of interest. This task ran as part of the DCASE challenge for the third time t
Externí odkaz:
http://arxiv.org/abs/2306.09223
Publikováno v:
Computing in Cardiology, vol. 49, 2022
This study presents our team PathToMyHeart's contribution to the George B. Moody PhysioNet Challenge 2022. Two models are implemented. The first model is a Dual Bayesian ResNet (DBRes), where each patient's recording is segmented into overlapping log
Externí odkaz:
http://arxiv.org/abs/2305.16691
Autor:
Nolasco, Inês, Singh, Shubhr, Morfi, Veronica, Lostanlen, Vincent, Strandburg-Peshkin, Ariana, Vidaña-Vila, Ester, Gill, Lisa, Pamuła, Hanna, Whitehead, Helen, Kiskin, Ivan, Jensen, Frants H., Morford, Joe, Emmerson, Michael G., Versace, Elisabetta, Grout, Emily, Liu, Haohe, Stowell, Dan
Automatic detection and classification of animal sounds has many applications in biodiversity monitoring and animal behaviour. In the past twenty years, the volume of digitised wildlife sound available has massively increased, and automatic classific
Externí odkaz:
http://arxiv.org/abs/2305.13210
Autor:
Budd, Jobie, Baker, Kieran, Karoune, Emma, Coppock, Harry, Patel, Selina, Cañadas, Ana Tendero, Titcomb, Alexander, Payne, Richard, Hurley, David, Egglestone, Sabrina, Butler, Lorraine, Mellor, Jonathon, Nicholson, George, Kiskin, Ivan, Koutra, Vasiliki, Jersakova, Radka, McKendry, Rachel A., Diggle, Peter, Richardson, Sylvia, Schuller, Björn W., Gilmour, Steven, Pigoli, Davide, Roberts, Stephen, Packham, Josef, Thornley, Tracey, Holmes, Chris
The UK COVID-19 Vocal Audio Dataset is designed for the training and evaluation of machine learning models that classify SARS-CoV-2 infection status or associated respiratory symptoms using vocal audio. The UK Health Security Agency recruited volunta
Externí odkaz:
http://arxiv.org/abs/2212.07738
Autor:
Coppock, Harry, Nicholson, George, Kiskin, Ivan, Koutra, Vasiliki, Baker, Kieran, Budd, Jobie, Payne, Richard, Karoune, Emma, Hurley, David, Titcomb, Alexander, Egglestone, Sabrina, Cañadas, Ana Tendero, Butler, Lorraine, Jersakova, Radka, Mellor, Jonathon, Patel, Selina, Thornley, Tracey, Diggle, Peter, Richardson, Sylvia, Packham, Josef, Schuller, Björn W., Pigoli, Davide, Gilmour, Steven, Roberts, Stephen, Holmes, Chris
Recent work has reported that AI classifiers trained on audio recordings can accurately predict severe acute respiratory syndrome coronavirus 2 (SARSCoV2) infection status. Here, we undertake a large scale study of audio-based deep learning classifie
Externí odkaz:
http://arxiv.org/abs/2212.08570
Autor:
Pigoli, Davide, Baker, Kieran, Budd, Jobie, Butler, Lorraine, Coppock, Harry, Egglestone, Sabrina, Gilmour, Steven G., Holmes, Chris, Hurley, David, Jersakova, Radka, Kiskin, Ivan, Koutra, Vasiliki, Mellor, Jonathon, Nicholson, George, Packham, Joe, Patel, Selina, Payne, Richard, Roberts, Stephen J., Schuller, Björn W., Tendero-Cañadas, Ana, Thornley, Tracey, Titcomb, Alexander
Since early in the coronavirus disease 2019 (COVID-19) pandemic, there has been interest in using artificial intelligence methods to predict COVID-19 infection status based on vocal audio signals, for example cough recordings. However, existing studi
Externí odkaz:
http://arxiv.org/abs/2212.08571
Autor:
Schuller, Björn W., Batliner, Anton, Amiriparian, Shahin, Bergler, Christian, Gerczuk, Maurice, Holz, Natalie, Larrouy-Maestri, Pauline, Bayerl, Sebastian P., Riedhammer, Korbinian, Mallol-Ragolta, Adria, Pateraki, Maria, Coppock, Harry, Kiskin, Ivan, Sinka, Marianne, Roberts, Stephen
The ACM Multimedia 2022 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the Vocalisations and Stuttering Sub-Challenges, a classification on huma
Externí odkaz:
http://arxiv.org/abs/2205.06799
Autor:
Kiskin, Ivan, Sinka, Marianne, Cobb, Adam D., Rafique, Waqas, Wang, Lawrence, Zilli, Davide, Gutteridge, Benjamin, Dam, Rinita, Marinos, Theodoros, Li, Yunpeng, Msaky, Dickson, Kaindoa, Emmanuel, Killeen, Gerard, Herreros-Moya, Eva, Willis, Kathy J., Roberts, Stephen J.
This paper presents the first large-scale multi-species dataset of acoustic recordings of mosquitoes tracked continuously in free flight. We present 20 hours of audio recordings that we have expertly labelled and tagged precisely in time. Significant
Externí odkaz:
http://arxiv.org/abs/2110.07607
Mosquitoes are the only known vector of malaria, which leads to hundreds of thousands of deaths each year. Understanding the number and location of potential mosquito vectors is of paramount importance to aid the reduction of malaria transmission cas
Externí odkaz:
http://arxiv.org/abs/2001.04733
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