Matthew Browne

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Remote monitoring of coastal conditions in locations of high public usage is a fast growing application of information technology. Remote mounted CCD camera systems provide a relatively cheap and potentially rich source of information on the state of the near-shore beach zone. The present paper presents a non-technical overview of a system for appropriate(More)
Convolutional neural networks (CNNs) represent an interesting method for adaptive image processing, and form a link between general feedforward neu-ral networks and adaptive filters. Two dimensional CNNs are formed by one or more layers of two dimensional filters, with possible non-linear activation functions and/or down-sampling. Conventional neural(More)
Detecting cracks is an important function in building , tunnel, and bridge structural analysis. Successful automation of crack detection can provide a uniform and timely means for preventing further damage to structures. This laboratory has successfully applied convolutional neural networks (CNNs) to on-line crack detection. CNNs represent an interesting(More)
BACKGROUND Independent mobility describes the freedom of children to travel and play in public spaces without adult supervision. The potential benefits for children are significant such as social interactions with peers, spatial and traffic safety skills and increased physical activity. Yet, the health benefits of independent mobility, particularly on(More)
The effectiveness of Savitzky–Golay type symmetric polynomial smoothers is known to be strongly dependent on the window size. Many authors note that selection of the appropriate window size is essential for achieving the correct trade-off between noise reduction and avoiding the introduction of bias. However, it is often overlooked that, in the case of(More)