AIMC Topic: Birds

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Exploring the spatiotemporal influence of climate on American avian migration with random forests.

Scientific reports Jul 1, 2025
Birds have adapted to climatic and ecological cycles to inform their Spring and Fall migration timings, but anthropogenic global warming has affected these long-establish cycles. Understanding these dynamics is critical for conservation during a chan...
Climate Animal Migration Machine Learning Animals Forests Seasons Birds Climate Change Spatio-Temporal Analysis Random Forest
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Enhancing occluded and standard bird object recognition using fuzzy-based ensembled computer vision approach with convolutional neural network.

Scientific reports Jul 1, 2025
Classifying bird species is essential for ecological study and biodiversity protection, currently, conventional approaches are frequently laborious and susceptible to mistakes. Convolutional Neural Networks (CNNs) provide a more reliable option for f...
Neural Networks, Computer Image Processing, Computer-Assisted Fuzzy Logic Pattern Recognition, Automated Animals Birds Convolutional Neural Networks
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Semen collection, semen analysis and artificial insemination in the kākāpō (Strigops habroptilus) to support its conservation.

PloS one May 9, 2025
The critically endangered kākāpō (Strigops habroptilus) has suffered population declines due to habitat loss, hunting, and predation. Conservation efforts, including translocation to predator-free islands, have helped increase numbers of this flightl...
Spermatozoa Male Female Fertility Birds Endangered Species Animals Insemination, Artificial Semen Analysis Conservation of Natural Resources
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Bio-inspired motion detection models for improved UAV and bird differentiation: a novel deep learning framework.

Scientific reports May 3, 2025
The rapid increase in Unmanned Aerial Vehicle (UAV) deployments has led to growing concerns about their detection and differentiation from birds, particularly in sensitive areas like airports. Existing detection systems often struggle to distinguish ...
Neural Networks, Computer Unmanned Aerial Devices Deep Learning Motion Flight, Animal Animals Birds
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Machine learning assessment of zoonotic potential in avian influenza viruses using PB2 segment.

BMC genomics Apr 23, 2025
BACKGROUND: Influenza A virus (IAV) is a major global health threat, causing seasonal epidemics and occasional pandemics. Particularly, Influenza A viruses from avian species pose significant zoonotic threats, with PB2 adaptation serving as a critica...
Risk Assessment Influenza in Birds Birds Machine Learning Animals Zoonoses RNA-Dependent RNA Polymerase Influenza A virus Mutation Viral Proteins Humans
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Delayed flowering phenology of red-flowering plants in response to hummingbird migration.

Current biology : CB Apr 14, 2025
The radiation of angiosperms is marked by a phenomenal diversity of floral size, shape, color, scent, and reward. The multi-dimensional response to selection to optimize pollination has generated correlated suites of these floral traits across distan...
Seasons Flowers Pollination Birds Color Animals Magnoliopsida North America Animal Migration Pigmentation
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Generative AI extracts ecological meaning from the complex three dimensional shapes of bird bills.

PLoS computational biology Mar 17, 2025
Data on the three dimensional shape of organismal morphology is becoming increasingly available, and forms part of a new revolution in high-throughput phenomics that promises to help understand ecological and evolutionary processes that influence phe...
Birds Deep Learning Imaging, Three-Dimensional Computational Biology Beak Artificial Intelligence Animals
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Identifying the combined impact of human activities and natural factors on China's avian species richness using interpretable machine learning methods.

Journal of environmental management Feb 15, 2025
With human activities-derived escalating climate change and rapid urbanization, avian species face significant survival challenges. Understanding the impact of human activities and environmental drivers on avian species richness is critical for effec...
Human Activities Climate Change Conservation of Natural Resources Humans Machine Learning Animals Birds China Biodiversity
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A framework for assessing reliability of observer annotations of aerial wildlife imagery, with insights for deep learning applications.

PloS one Jan 15, 2025
There is growing interest in using deep learning models to automate wildlife detection in aerial imaging surveys to increase efficiency, but human-generated annotations remain necessary for model training. However, even skilled observers may diverge ...
New Mexico Ducks Animals, Wild Deep Learning Image Processing, Computer-Assisted Animals Birds Humans Reproducibility of Results
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Exploring the impact of land use on bird diversity in high-density urban areas using explainable machine learning models.

Journal of environmental management Jan 11, 2025
Amid rapid urbanization, land use shifts in cities globally have profound effects on ecosystems and biodiversity. Birds, as a crucial component of urban biodiversity, are highly sensitive to environmental changes and often serve as indicator species ...
Machine Learning Animals Ecosystem Birds Biodiversity Conservation of Natural Resources China Urbanization Cities
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