A convolutional neural network for automatic analysis of aerial imagery
Maire, Frederic, Mejias, Luis, & Hodgson, Amanda (2014) A convolutional neural network for automatic analysis of aerial imagery. In Wang, Lei Wang, Ogunbona, Philip, & Li, Wanqing (Eds.) Digital Image Computing: Techniques and Applications (DICTA 2014), 25-27 November 2014, Wollongong, New South Wales, Australia.
This paper introduces a new method to automate the detection of marine species in aerial imagery using a Machine Learning approach. Our proposed system has at its core, a convolutional neural network. We compare this trainable classifier to a handcrafted classifier based on color features, entropy and shape analysis. Experiments demonstrate that the convolutional neural network outperforms the handcrafted solution. We also introduce a negative training example-selection method for situations where the original training set consists of a collection of labeled images in which the objects of interest (positive examples) have been marked by a bounding box. We show that picking random rectangles from the background is not necessarily the best way to generate useful negative examples with respect to learning.
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|Item Type:||Conference Paper|
|Keywords:||Convolutional Neural Network, Image processing, Marine mammals, machine learning|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2014 IEEE|
|Copyright Statement:||Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.|
|Deposited On:||09 Oct 2014 22:45|
|Last Modified:||30 Jan 2015 14:31|
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