North Atlantic Right Whales Up-call Detection Using Multimodel Deep Learning

by   Ali K Ibrahim, et al.

A new method for North Atlantic Right Whales (NARW) up-call detection using Multimodel Deep Learning (MMDL) is presented in this paper. In this approach, signals from passive acoustic sensors are first converted to spectrogram and scalogram images, which are time-frequency representations of the signals. These images are in turn used to train an MMDL detec-tor, consisting of Convolutional Neural Networks (CNNs) and Stacked Auto Encoders (SAEs). Our experimental studies revealed that CNNs work better with spectrograms and SAEs with sca-lograms. Therefore in our experimental design, the CNNs are trained by using spectrogram im-ages, and the SAEs are trained by using scalogram images. A fusion mechanism is used to fuse the results from individual neural networks. In this paper, the results obtained from the MMDL detector are compared with those obtained from conventional machine learning algorithms trained with handcraft features. It is shown that the performance of the MMDL detector is sig-nificantly better than those of the representative conventional machine learning methods in terms of up-call detection rate, non-up-call detection rate, and false alarm rate.


page 8

page 9

page 11


A Vehicle Detection Approach using Deep Learning Methodologies

The purpose of this study is to successfully train our vehicle detector ...

Performance of a Deep Neural Network at Detecting North Atlantic Right Whale Upcalls

Passive acoustics provides a powerful tool for monitoring the endangered...

CNNs are Myopic

We claim that Convolutional Neural Networks (CNNs) learn to classify ima...

Android Botnet Detection using Convolutional Neural Networks

Today, Android devices are able to provide various services. They suppor...

Machine Learning For Distributed Acoustic Sensors, Classic versus Image and Deep Neural Networks Approach

Distributed Acoustic Sensing (DAS) using fiber optic cables is a promisi...

SVM-Based Sea-Surface Small Target Detection: A False-Alarm-Rate-Controllable Approach

In this letter, we consider the varying detection environments to addres...

Mosquito Detection with Neural Networks: The Buzz of Deep Learning

Many real-world time-series analysis problems are characterised by scarc...