Results 1 - 10 of 137

Application of wavelets to the pre-processing ofunderwater sounds

by K. J. Powell, T. Sapatinas, T. C. Bailey, W. J. Krzanowski , 1994
"... In this paper we consider data on underwater sounds of differing types. Our objective isto filter background noise and achieve an acceptable vel of reduction in the raw data, whilst at the same time maintaining the main features of the original signal. In particular, we consider data compression thr ..."
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In this paper we consider data on underwater sounds of differing types. Our objective isto filter background noise and achieve an acceptable vel of reduction in the raw data, whilst at the same time maintaining the main features of the original signal. In particular, we consider data compression

Time Series Data Analysis and Pre-process on

by Large Databases Gongde, Gongde Guo, Hui Wang, David Bell , 2002
"... In this paper we introduce a novel classification algorithm called MCC (Minimal Cover Classification), which works well for numerical data and categorical data. Given a new data tuple, it provides values for each class that measures the likelihood of the tuple belonging to that class. We then apply ..."
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in the time domain. The experimental result shows that the MCC algorithm is comparable to C4.5. Using MCC as a mining algorithm to predict the `upward' or `downward' trend of k-day stock returns, the average hit rate on pre-processed data is 20.55% higher than that on the original data. This means

Singleton Consistencies

by Patrick Prosser, Kostas Stergiou, Toby Walsh , 2000
"... We perform a comprehensive theoretical and empirical study of the bene ts of singleton consistencies. Our theoretical results help place singleton consistencies within the hierarchy of local consistencies. To determine the practical value of these theoretical results, we measured the cost-effectiven ..."
Abstract - Cited by 49 (9 self) - Add to MetaCart
-effectiveness of pre-processing with singleton consistency algorithms. Our experiments use both random and structured problems. Whilst pre-processing with singleton consistencies is not in general beneficial for random problems, it starts to pay off when randomness and structure are combined, and it is very worthwhile

STRUCTURAL CHARACTERISATION OF PRE-PROCESSED THERMOPLASTIC PROTEIN DERIVED FROM BLOODMEAL

by J. M. Bier, C. J. R. Verbeek, M. C. Lay
"... Additives are required to convert bloodmeal powder into an extrudable thermoplastic protein-based bioplastic. These include a protein denaturant, a surfactant, a reducing agent and plasticisers. The objective of this work was to assess the structural changes induced in bloodmeal by these additives p ..."
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, representing carbonyl group stretching in the protein backbone) is known to depend on protein secondary structures. Bloodmeal showed a broad, convoluted peak in this region, with a maximum in the range 1648 – 1658 cm-1, associated with α-helices. With processing additives, a dip was seen in the α-helix region

(or check DOI link for updated information) Interactions between Pre-Processing and Classification Methods for Event-Related-Potential Classification: Best-Practice Guidelines for Brain-Computer Interfacing

by Jason Farquhar, N. Jeremy Hill, Jason Farquhar, N. Jeremy Hill , 2012
"... Abstract Detecting event related potentials (ERPs) from single trials is crit-ical to the operation of many stimulus-driven brain computer interface (BCI) systems. The low strength of the ERP signal compared to the noise (due to artifacts and BCI irrelevant brain processes) makes this a challenging ..."
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Abstract Detecting event related potentials (ERPs) from single trials is crit-ical to the operation of many stimulus-driven brain computer interface (BCI) systems. The low strength of the ERP signal compared to the noise (due to artifacts and BCI irrelevant brain processes) makes this a challenging

Event Related Potentials and the Musical Brain: The Effects of Music Preference and Music Training on Pre-attentive Stimulus Recognition (N200) and Memory Updating (P300) Processes

by George N. Caldwell, Leigh M. Riby
"... Previous behavioural research has consistently found enhanced cognitive function whilst listening to classical music; the so called Mozart Effect (Rauscher et al, 1993). However, to date it has proven difficult to draw firm conclusions from this literature because of the diversity of methods used. I ..."
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Previous behavioural research has consistently found enhanced cognitive function whilst listening to classical music; the so called Mozart Effect (Rauscher et al, 1993). However, to date it has proven difficult to draw firm conclusions from this literature because of the diversity of methods used

Implicit Feature Selection with the Value Difference Metric

by Terry R. Payne, Peter Edwards
"... The nearest neighbour paradigm provides an effective approach to supervised learning. However, it is especially susceptible to the presence of irrelevant attributes. Whilst many approaches have been proposed that select only the most relevant attributes within a data set, these approaches involve ..."
Abstract - Cited by 14 (2 self) - Add to MetaCart
pre-processing the data in some way, and can often be computationally complex. The Value Difference Metric (VDM) is a symbolic distance metric used by a number of different nearest neighbour learning algorithms. This paper demonstrates how the VDM can be used to reduce the impact of irrelevant

Face Tracking and Pose Representation

by Stephen Mckenna, Shaogang Gong, J. J. Collins - In BMVC , 1996
"... We describe a dynamic face tracking system based on an integrated motion-based object tracking and model-based face detection framework. The motion-based tracker focuses attention for the face detector whilst the latter aids the tracking process. The system produces segmented face sequences from com ..."
Abstract - Cited by 23 (4 self) - Add to MetaCart
We describe a dynamic face tracking system based on an integrated motion-based object tracking and model-based face detection framework. The motion-based tracker focuses attention for the face detector whilst the latter aids the tracking process. The system produces segmented face sequences from

Time Normalization of LPC Feature Using Warping Method

by Rubita Sudirman, Sh. Hussain Salleh, Puspa Inayat Khalid, Abd Hamid Ahmad - Proceedings of the International Joint Conference on Neural Networks , 2005
"... This paper presents pre-processing of input features to artificial neural network (NN). This is for preparation of reliable reference templates for the set of words to be recognized. The processed features are pitch and Linear Predictive Coefficients (LPC) for input and reference templates, based on ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
This paper presents pre-processing of input features to artificial neural network (NN). This is for preparation of reliable reference templates for the set of words to be recognized. The processed features are pitch and Linear Predictive Coefficients (LPC) for input and reference templates, based

Annotated Free-Hand Sketches for Video Retrieval Using Object Semantics and Motion

by Rui Hu, Stuart James, John Collomosse , 2012
"... Abstract. We present a novel video retrieval system that accepts annotated free-hand sketches as queries. Existing sketch based video retrieval (SBVR) systems enable the appearance and movements of objects to be searched naturally through pictorial representations. Whilst visually expressive, such s ..."
Abstract - Cited by 2 (1 self) - Add to MetaCart
are applied to pre-process each clip into a video object representation that we augment with object classification and colour infor-mation. The result is a system capable of searching videos based on the desired colour, motion path, and semantic labels of the objects present. We evaluate the performance
Results 1 - 10 of 137