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Modelling Animal Biodiversity Using Acoustic Monitoring and Deep Learning
For centuries researchers have used sound to monitor and study wildlife.
BMI: A Behavior Measurement Indicator for Fuel Poverty Using Aggregated Load Readings from Smart Meters
Fuel poverty affects between 50 and 125 million households in Europe and is a significant issue for both developed and developing countries globally.
Conservation AI: Live Stream Analysis for the Detection of Endangered Species Using Convolutional Neural Networks and Drone Technology
Using a robust deep learning pipeline, a convolutional neural network is trained and implemented to detect rhinos and cars (considered an important tool in poaching for fast access and artefact transportation in natural habitats) in the study, that are found within live video streamed from drones Transfer learning with the Faster RCNN Resnet 101 is performed to train a custom model with 350 images of rhinos and 350 images of cars.
Detecting Activities of Daily Living and Routine Behaviours in Dementia Patients Living Alone Using Smart Meter Load Disaggregation
While the Decision Forest achieved (AUC=0. 9429, Sen=0. 9634 and Spec=0. 9634).
