AIMC Topic: Cetacea
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A new strategy for groundwater level prediction using a hybrid deep learning model under Ecological Water Replenishment.
Environmental science and pollution research international
Mar 4, 2024
Accurate prediction of the groundwater level (GWL) is crucial for sustainable groundwater resource management. Ecological water replenishment (EWR) involves artificially diverting water to replenish the ecological flow and water resources of both sur...
An innovative ensemble model based on deep learning for predicting COVID-19 infection.
Scientific reports
Jul 29, 2023
Nowadays, global public health crises are occurring more frequently, and accurate prediction of these diseases can reduce the burden on the healthcare system. Taking COVID-19 as an example, accurate prediction of infection can assist experts in effec...
An expert-based system to predict population survival rate from health data.
Conservation biology : the journal of the Society for Conservation Biology
Apr 10, 2023
Timely detection and understanding of causes for population decline are essential for effective wildlife management and conservation. Assessing trends in population size has been the standard approach, but we propose that monitoring population health...
A novel hybrid optimization enabled robust CNN algorithm for an IoT network intrusion detection approach.
PloS one
Dec 1, 2022
Due to the huge number of connected Internet of Things (IoT) devices within a network, denial of service and flooding attacks on networks are on the rise. IoT devices are disrupted and denied service because of these attacks. In this study, we propos...
A machine learning pipeline for classification of cetacean echolocation clicks in large underwater acoustic datasets.
PLoS computational biology
Dec 3, 2021
Machine learning algorithms, including recent advances in deep learning, are promising for tools for detection and classification of broadband high frequency signals in passive acoustic recordings. However, these methods are generally data-hungry and...
Aerial-trained deep learning networks for surveying cetaceans from satellite imagery.
PloS one
Oct 1, 2019
Most cetacean species are wide-ranging and highly mobile, creating significant challenges for researchers by limiting the scope of data that can be collected and leaving large areas un-surveyed. Aerial surveys have proven an effective way to locate a...
Silbido profundo: An open source package for the use of deep learning to detect odontocete whistles.
The Journal of the Acoustical Society of America
Dec 1, 2022
This work presents an open-source matlab software package for exploiting recent advances in extracting tonal signals from large acoustic data sets. A whistle extraction algorithm published by Li, Liu, Palmer, Fleishman, Gillespie, Nosal, Shiu, Klinck...
Convolutional neural network for detecting odontocete echolocation clicks.
The Journal of the Acoustical Society of America
Jan 1, 2019
In this work, a convolutional neural network based method is proposed to automatically detect odontocetes echolocation clicks by analyzing acoustic data recordings from a passive acoustic monitoring system. The neural network was trained to distingui...
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