AIMC Topic: Animals, Wild

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Understanding External Influences on Target Detection and Classification Using Camera Trap Images and Machine Learning.

Sensors (Basel, Switzerland) Jul 19, 2022
Using machine learning (ML) to automate camera trap (CT) image processing is advantageous for time-sensitive applications. However, little is currently known about the factors influencing such processing. Here, we evaluate the influence of occlusion,...
Image Processing, Computer-Assisted Biodiversity Animals Animals, Wild Humans Machine Learning
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Is the use of deep learning an appropriate means to locate debris in the ocean without harming aquatic wildlife?

Marine pollution bulletin Jul 1, 2022
With the global issue of marine debris ever expanding, it is imperative that the technology industry steps in. The aim is to find if deep learning can successfully distinguish between marine life and synthetic debris underwater. This study assesses w...
Artificial Intelligence Animals, Wild Deep Learning Oceans and Seas Animals Ecosystem
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Intelligent Systems Using Sensors and/or Machine Learning to Mitigate Wildlife-Vehicle Collisions: A Review, Challenges, and New Perspectives.

Sensors (Basel, Switzerland) Mar 23, 2022
Worldwide, the persistent trend of human and animal life losses, as well as damage to properties due to wildlife-vehicle collisions (WVCs) remains a significant source of concerns for a broad range of stakeholders. To mitigate their occurrences and i...
Technology Animals Animals, Wild Artificial Intelligence Machine Learning Algorithms
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Perspectives in machine learning for wildlife conservation.

Nature communications Feb 9, 2022
Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently distill dat...
Machine Learning Animals Models, Theoretical Ecology Automation Ecosystem Animals, Wild Conservation of Natural Resources Knowledge
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Comparing Class-Aware and Pairwise Loss Functions for Deep Metric Learning in Wildlife Re-Identification.

Sensors (Basel, Switzerland) Sep 12, 2021
Similarity learning using deep convolutional neural networks has been applied extensively in solving computer vision problems. This attraction is supported by its success in one-shot and zero-shot classification applications. The advances in similari...
Awareness Animals, Wild Attention Neural Networks, Computer Animals
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Graph Regularized Flow Attention Network for Video Animal Counting From Drones.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Jun 3, 2021
In this paper, we propose a large-scale video based animal counting dataset collected by drones (AnimalDrone) for agriculture and wildlife protection. The dataset consists of two subsets, i.e., PartA captured on site by drones and PartB collected fro...
Data Collection Video Recording Crowding Animals, Wild Image Processing, Computer-Assisted Agriculture Databases, Factual Animals Artificial Intelligence Algorithms
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The African wildlife ontology tutorial ontologies.

Journal of biomedical semantics Jun 23, 2020
BACKGROUND: Most tutorial ontologies focus on illustrating one aspect of ontology development, notably language features and automated reasoners, but ignore ontology development factors, such as emergent modelling guidelines and ontological principle...
Animals, Wild Africa Biological Ontologies Language Animals
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Machine learning goes wild: Using data from captive individuals to infer wildlife behaviours.

PloS one May 5, 2020
1. Remotely tracking distinct behaviours of animals using acceleration data and machine learning has been carried out successfully in several species in captive settings. In order to study the ecology of animals in natural habitats, such behaviour cl...
Humans Neural Networks, Computer Algorithms Animals Behavior, Animal Machine Learning Animals, Wild Support Vector Machine
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Artificial intelligence and avian influenza: Using machine learning to enhance active surveillance for avian influenza viruses.

Transboundary and emerging diseases Aug 19, 2019
Influenza A viruses are one of the most significant viral groups globally with substantial impacts on human, domestic animal and wildlife health. Wild birds are the natural reservoirs for these viruses, and active surveillance within wild bird popula...
Animals Influenza in Birds Birds Population Surveillance Artificial Intelligence Animals, Wild Polymerase Chain Reaction Machine Learning United States Disease Reservoirs
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Insights and approaches using deep learning to classify wildlife.

Scientific reports May 31, 2019
The implementation of intelligent software to identify and classify objects and individuals in visual fields is a technology of growing importance to operatives in many fields, including wildlife conservation and management. To non-experts, the metho...
Pattern Recognition, Automated Animals, Wild Species Specificity Algorithms Africa Biodiversity Image Processing, Computer-Assisted Reproducibility of Results Ecology Computer Graphics Cluster Analysis Deep Learning Neural Networks, Computer Animals Software
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