AIMC Topic: Echolocation
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Multiclass CNN Approach for Automatic Classification of Dolphin Vocalizations.
Sensors (Basel, Switzerland)
Apr 16, 2025
Monitoring dolphins in the open sea is essential for understanding their behavior and the impact of human activities on the marine ecosystems. Passive Acoustic Monitoring (PAM) is a non-invasive technique for tracking dolphins, providing continuous d...
Bat2Web: A Framework for Real-Time Classification of Bat Species Echolocation Signals Using Audio Sensor Data.
Sensors (Basel, Switzerland)
May 1, 2024
Bats play a pivotal role in maintaining ecological balance, and studying their behaviors offers vital insights into environmental health and aids in conservation efforts. Determining the presence of various bat species in an environment is essential ...
Small-scale location identification in natural environments with deep learning based on biomimetic sonar echoes.
Bioinspiration & biomimetics
Feb 13, 2023
Many bat species navigate in complex, heavily vegetated habitats. To achieve this, the animal relies on a sensory basis that is very different from what is typically done in engineered systems that are designed for outdoor navigation. Whereas the eng...
Large-scale recognition of natural landmarks with deep learning based on biomimetic sonar echoes.
Bioinspiration & biomimetics
Feb 11, 2022
The ability to identify natural landmarks on a regional scale could contribute to the navigation skills of echolocating bats and also advance the quest for autonomy in natural environments with man-made systems. However, recognizing natural landmarks...
A machine learning pipeline for classification of cetacean echolocation clicks in large underwater acoustic datasets.
PLoS computational biology
Dec 3, 2021
Machine learning algorithms, including recent advances in deep learning, are promising for tools for detection and classification of broadband high frequency signals in passive acoustic recordings. However, these methods are generally data-hungry and...
A biomimetic soft robotic pinna for emulating dynamic reception behavior of horseshoe bats.
Bioinspiration & biomimetics
Dec 7, 2020
Encoding of sensory information is fundamental to closing the performance gap between man-made and biological sensing. It has been hypothesized that the coupling of sensing and actuation, a phenomenon observed in bats among other species, is critical...
Avoidance of non-localizable obstacles in echolocating bats: A robotic model.
PLoS computational biology
Dec 19, 2019
Most objects and vegetation making up the habitats of echolocating bats return a multitude of overlapping echoes. Recent evidence suggests that the limited temporal and spatial resolution of bio-sonar prevents bats from separately perceiving the obje...
Comparing context-dependent call sequences employing machine learning methods: an indication of syntactic structure of greater horseshoe bats.
The Journal of experimental biology
Dec 18, 2019
For analysis of vocal syntax, accurate classification of call sequence structures in different behavioural contexts is essential. However, an effective, intelligent program for classifying call sequences from numerous recorded sound files is still la...
Robust sound event detection in bioacoustic sensor networks.
PloS one
Oct 24, 2019
Bioacoustic sensors, sometimes known as autonomous recording units (ARUs), can record sounds of wildlife over long periods of time in scalable and minimally invasive ways. Deriving per-species abundance estimates from these sensors requires detection...
Deep Machine Learning Techniques for the Detection and Classification of Sperm Whale Bioacoustics.
Scientific reports
Aug 29, 2019
We implemented Machine Learning (ML) techniques to advance the study of sperm whale (Physeter macrocephalus) bioacoustics. This entailed employing Convolutional Neural Networks (CNNs) to construct an echolocation click detector designed to classify s...
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