39 citations · 68 across the 6 of their papers we have counts for
7 papers
The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitoes
Björn W. Schuller, Anton Batliner, Shahin Amiriparian +12
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…
HumBugDB: A Large-scale Acoustic Mosquito Dataset
Ivan Kiskin, Marianne Sinka, Adam D. Cobb +13
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 th…
HumBug Zooniverse: a crowd-sourced acoustic mosquito dataset
Ivan Kiskin, Adam D. Cobb, Lawrence Wang +1
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…
Super-resolution of Time-series Labels for Bootstrapped Event Detection
Ivan Kiskin, Udeepa Meepegama, Steven Roberts
Solving real-world problems, particularly with deep learning, relies on the availability of abundant, quality data. In this paper we develop a novel framework that maximises the ut…
Cost-sensitive detection with variational autoencoders for environmental acoustic sensing
Yunpeng Li, Ivan Kiskin, Davide Zilli +4
Environmental acoustic sensing involves the retrieval and processing of audio signals to better understand our surroundings. While large-scale acoustic data make manual analysis in…
Mosquito detection with low-cost smartphones: data acquisition for malaria research
Yunpeng Li, Davide Zilli, Henry Chan +4
Mosquitoes are a major vector for malaria, causing hundreds of thousands of deaths in the developing world each year. Not only is the prevention of mosquito bites of paramount impo…
Mosquito Detection with Neural Networks: The Buzz of Deep Learning
Ivan Kiskin, Bernardo Pérez Orozco, Theo Windebank +4
Many real-world time-series analysis problems are characterised by scarce data. Solutions typically rely on hand-crafted features extracted from the time or frequency domain allied…