15 citations · 21 across the 4 of their papers we have counts for
4 papers
Enhancing Orthopox Image Classification Using Hybrid Machine Learning and Deep Learning Models
Alejandro Puente-Castro, Enrique Fernandez-Blanco, Daniel Rivero +1
Orthopoxvirus infections must be accurately classified from medical pictures for an easy and early diagnosis and epidemic prevention. The necessity for automated and scalable solut…
Harmful algal bloom forecasting. A comparison between stream and batch learning
Andres Molares-Ulloa, Elisabet Rocruz, Daniel Rivero +4
Diarrhetic Shellfish Poisoning (DSP) is a global health threat arising from shellfish contaminated with toxins produced by dinoflagellates. The condition, with its widespread incid…
Hybrid Machine Learning techniques in the management of harmful algal blooms impact
Andres Molares-Ulloa, Daniel Rivero, Jesus Gil Ruiz +2
Harmful algal blooms (HABs) are episodes of high concentrations of algae that are potentially toxic for human consumption. Mollusc farming can be affected by HABs because, as filte…
Machine Learning in management of precautionary closures caused by lipophilic biotoxins
Andres Molares-Ulloa, Enrique Fernandez-Blanco, Alejandro Pazos +1
Mussel farming is one of the most important aquaculture industries. The main risk to mussel farming is harmful algal blooms (HABs), which pose a risk to human consumption. In Galic…