AIMC Topic: Echolocation

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A fully autonomous terrestrial bat-like acoustic robot.

PLoS computational biology Sep 6, 2018
Echolocating bats rely on active sound emission (echolocation) for mapping novel environments and navigating through them. Many theoretical frameworks have been suggested to explain how they do so, but few attempts have been made to build an actual r...
Chiroptera Predatory Behavior Sound Echolocation Decision Making Acoustics Robotics Reproducibility of Results Animals Algorithms Neural Networks, Computer
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Bat detective-Deep learning tools for bat acoustic signal detection.

PLoS computational biology Mar 8, 2018
Passive acoustic sensing has emerged as a powerful tool for quantifying anthropogenic impacts on biodiversity, especially for echolocating bat species. To better assess bat population trends there is a critical need for accurate, reliable, and open s...
Echolocation Signal Processing, Computer-Assisted Algorithms Chiroptera Neural Networks, Computer Environmental Monitoring Endangered Species Computational Biology Zoology Machine Learning Animals
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The development of deep convolutional generative adversarial network to synthesize odontocetes' clicks.

The Journal of the Acoustical Society of America Jan 1, 2025
Odontocetes are capable of dynamically changing their echolocation clicks to efficiently detect targets, and learning their clicking strategy can facilitate the design of man-made detecting signals. In this study, we developed deep convolutional gene...
Sound Spectrography Bottle-Nosed Dolphin Acoustics Generative Adversarial Networks Animals Porpoises Signal Processing, Computer-Assisted Echolocation Deep Learning Vocalization, Animal Neural Networks, Computer
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Convolutional neural network for detecting odontocete echolocation clicks.

The Journal of the Acoustical Society of America Jan 1, 2019
In this work, a convolutional neural network based method is proposed to automatically detect odontocetes echolocation clicks by analyzing acoustic data recordings from a passive acoustic monitoring system. The neural network was trained to distingui...
Animals Vocalization, Animal Neural Networks, Computer Cetacea Echolocation
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Compensating for the effects of site and equipment variation on delphinid species identification from their echolocation clicks.

The Journal of the Acoustical Society of America Jan 1, 2015
A concern for applications of machine learning techniques to bioacoustics is whether or not classifiers learn the categories for which they were trained. Unfortunately, information such as characteristics of specific recording equipment or noise envi...
Echolocation Monte Carlo Method Subtraction Technique Pacific Ocean Sound Spectrography Transducers Species Specificity Fourier Analysis Pattern Recognition, Automated Algorithms Normal Distribution Machine Learning Dolphins Animals
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