Results 11 to 20 of about 7,109 (152)
Multi-Scale Deep Feature Fusion with Machine Learning Classifier for Birdsong Classification
Applied SciencesBirds are significant bioindicators in the assessment of habitat biodiversity, ecological impacts and ecosystem health. Against the backdrop of easier bird vocalization data acquisition, and with deep learning and machine learning technologies as the ...
Wei Li +6 more
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Applied SciencesBirdsong classification plays a crucial role in monitoring species distribution, population structure, and environmental changes. Existing methods typically use supervised learning to extract specific features for classification, but this may limit the ...
Ziyi Wang +4 more
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Integrative ZoologyABSTRACT Birds play a critical role in maintaining ecological balance and serve as key indicators of biodiversity. Observing bird behavior in natural environments poses significant challenges. However, identifying bird songs through sensor technology provides a non‐invasive and environmentally friendly method for ...
Qin Zhang +8 more
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Deep learning bird song recognition based on MFF-ScSEnet
Ecological Indicators, 2023 Bird diversity plays an important role in ecological balance, and bird song identification is of great practical significance. The spectrum generated by feature extraction shows good performance on classification.
Shipeng Hu +5 more
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NIPS4Bplus: a richly annotated birdsong audio dataset [PDF]
PeerJ Computer Science, 2019 Recent advances in birdsong detection and classification have approached a limit due to the lack of fully annotated recordings. In this paper, we present NIPS4Bplus, the first richly annotated birdsong audio dataset, that is comprised of recordings ...
Veronica Morfi +4 more
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Birdsong Phrase Verification and Classification Using Siamese Neural Networks [PDF]
, 2021 AbstractThe process of learning good features to discriminate among numerous and different bird phrases is computationally expensive. Moreover, it might be impossible to achieve acceptable performance in cases where training data is scarce and classes are unbalanced.
Santiago Rentería +2 more
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Automatic Recognition of Element Classes and Boundaries in the Birdsong with Variable Sequences. [PDF]
PLoS ONE, 2016 Researches on sequential vocalization often require analysis of vocalizations in long continuous sounds. In such studies as developmental ones or studies across generations in which days or months of vocalizations must be analyzed, methods for automatic ...
Takuya Koumura, Kazuo Okanoya
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Avian Research, 2023 Dialects are a specific form of geographic variation of birdsong with relatively sharp boundaries between distinct song characteristics, which provide opportunities for focused studies of processes underlying the emergence of spatial patterns in ...
Lucie Diblíková +4 more
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Machine Learning-based Classification of Birds through Birdsong
, 2022 Audio sound recognition and classification is used for many tasks and applications including human voice recognition, music recognition and audio tagging. In this paper we apply Mel Frequency Cepstral Coefficients (MFCC) in combination with a range of machine learning models to identify (Australian) birds from publicly available audio files of their ...
Chang, Yueying, Sinnott, Richard O.
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A hierarchical birdsong feature extraction architecture combining static and dynamic modeling
Ecological Indicators, 2023 To conserve bird biodiversity and monitor the distribution of species in the region, it is of tremendous necessity to identify birds by their songs and explore the rich ecological information birdsong contains.
Yanan Wang +5 more
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