Transcription of Image Classification Using Convolutional Neural Networks
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Image Classification Using Convolutional Neural Networks
International Journal of Advancements in Research & Technology, Volume 3, Issue 6, June-2014 1661 ISSN 2278-7763 IJSER 2014 Image Classification Using Convolutional Neural Networks Deepika Jaswal, , Abstract Deep Learning has emerged as a new area in machine learning and is applied to a number of signal and Image main purpose of the work presented in this paper, is to apply the concept of a Deep Learning algorithm namely, Convolutional Neural Networks (CNN) in Image Classification . The algorithm is tested on various standard datasets, like remote sensing data of aerial images (UC Merced Land Use Dataset) and scene images from SUN database.
Convolutional Neural Networks (CNN) is variants of Mu. l. ti - Layer Perceptron (MLPs) which are inspired from biology. These filters are local in input space and are thus better suited to exploit the strong spatially local correlation present in natu-ral images [5]. Convolutional neural networks are designed to
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