Animal Sound Identifier (ASI): software for automated identification of vocal animals
Published 2018 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Animal Sound Identifier (ASI): software for automated identification of vocal animals
Authors
Keywords
-
Journal
ECOLOGY LETTERS
Volume 21, Issue 8, Pages 1244-1254
Publisher
Wiley
Online
2018-06-25
DOI
10.1111/ele.13092
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification
- (2017) Justin Salamon et al. IEEE SIGNAL PROCESSING LETTERS
- Comparison of semiautomated bird song recognition with manual detection of recorded bird song samples
- (2017) Lisa A. Venier et al. Avian Conservation and Ecology
- Autonomous recording units in avian ecological research: current use and future applications
- (2017) Julia Shonfield et al. Avian Conservation and Ecology
- PROTAX-Sound: A probabilistic framework for automated animal sound identification
- (2017) Ulisses Moliterno de Camargo et al. PLoS One
- Non-invasive acoustic detection of wolves
- (2016) Stefan M. Suter et al. BIOACOUSTICS-THE INTERNATIONAL JOURNAL OF ANIMAL SOUND AND ITS RECORDING
- Tools for automated acoustic monitoring within the R package monitoR
- (2016) Jonathan Katz et al. BIOACOUSTICS-THE INTERNATIONAL JOURNAL OF ANIMAL SOUND AND ITS RECORDING
- Counting chirps: acoustic monitoring of cryptic frogs
- (2016) G. John Measey et al. JOURNAL OF APPLIED ECOLOGY
- Improving distribution data of threatened species by combining acoustic monitoring and occupancy modelling
- (2016) Marconi Campos-Cerqueira et al. Methods in Ecology and Evolution
- Autonomous sound monitoring shows higher use of Amazon old growth than secondary forest by parrots
- (2015) Luiza Figueira et al. BIOLOGICAL CONSERVATION
- Automatic Classification of a Taxon-Rich Community Recorded in the Wild
- (2014) Ilyas Potamitis PLoS One
- Random Forest for improved analysis efficiency in passive acoustic monitoring
- (2013) Jesse C. Ross et al. Ecological Informatics
- A practical comparison of manual and autonomous methods for acoustic monitoring
- (2013) Andrew Digby et al. Methods in Ecology and Evolution
- Real-time bioacoustics monitoring and automated species identification
- (2013) T. Mitchell Aide et al. PeerJ
- Acoustic classification of multiple simultaneous bird species: A multi-instance multi-label approach
- (2012) Forrest Briggs et al. JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA
- Using occupancy estimates to fine-tune conservation concerns
- (2010) G. Ferraz et al. ANIMAL CONSERVATION
- A comparison of supervised learning techniques in the classification of bat echolocation calls
- (2010) David W. Armitage et al. Ecological Informatics
- Coefficients of Determination in Logistic Regression Models—A New Proposal: The Coefficient of Discrimination
- (2009) Tue Tjur AMERICAN STATISTICIAN
- Old growth and secondary forest site occupancy by nocturnal birds in a neotropical landscape
- (2009) M. Sberze et al. ANIMAL CONSERVATION
- The influence of the acoustic community on songs of birds in a neotropical rain forest
- (2009) David Luther BEHAVIORAL ECOLOGY
- Automated classification of bird and amphibian calls using machine learning: A comparison of methods
- (2009) Miguel A. Acevedo et al. Ecological Informatics
- Similarity Search in Animal Sound Databases
- (2009) R. Bardeli IEEE TRANSACTIONS ON MULTIMEDIA
- EFFECTS OF VEGETATION AND BACKGROUND NOISE ON THE DETECTION PROCESS IN AUDITORY AVIAN POINT-COUNT SURVEYS
- (2008) KRISHNA PACIFICI et al. AUK
- What you see is not what you get: the role of ultrasonic detectors in increasing inventory completeness in Neotropical bat assemblages
- (2008) M. Cristina MacSwiney G. et al. JOURNAL OF APPLIED ECOLOGY
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started