We propose GEML, a novel detection approach based on evolutionary machine learning using software properties of diverse nature. Firstly, GEML makes use of an evolutionary algorithm to extract those characteristics that better describe the DP, formulated in terms of human-readable rules, whose syntax...
Pre-processing might also be performed in order to speed up computation. For example, if the goal is real-time face detection in a high-resolution video stream, the computer must handle huge numbers of pixels per second, and presenting these directly to a complex pattern recognition algorithm m...
A machine learning perspective on the development of clinical decision support systems utilizing mass spectra of blood samples Recently, pattern analysis of multiple biomarkers in blood samples has attracted attention as an alternative to the usage of a single biomarker for early detection of cancer. ...
Marchette:ComputerIntrusionDetectionandNetworkMonitoring: AStatisticalViewpoint. RubinsteinandKroese:TheCross-EntropyMethod:AUnifiedApproachto CombinatorialOptimization,MonteCarloSimulation,andMachineLearning. Studený:ProbabilisticConditionalIndependenceStructures. ...
Machine Learning vs. Deep Learning | Introduction to Deep Learning A common application of pattern recognition in engineering is defect detection in manufacturing to improve product quality while reducing production costs in industrial applications. The figure below shows howcompanies use vision-based techn...
as long as it works correctly. However, technologies such as filters, boundary detection, and morphological processing have shown to be effective when applied to an image detection algorithm. Researchers in the pattern recognition community showed an increasing interest in this topic, spawning the fiel...
Outlier Detection CBOF: Cohesiveness-Based Outlier Factor A Novel Definition of Outlier-ness Vineet Joshi, Raj Bhatnagar Pages 175-189 A New Measure of Outlier Detection Performance Kliton Andrea, Georgy Shevlyakov, Natalia Vassilieva, Alexander Ulanov Pages 190-197 ...
we can use any machine learning method to recognize falls. This theory allows us to use a parsimonious AI model to effect extremely efficient processing of videos at a high frame rate to combat the challenges currently faced in fall detection accuracy, computational efficiency, and financial cost....
Living systems are constantly engaged in computational processes such as signal detection, processing, and decision making to perform sophisticated tasks. For example, in the vertebrate adaptive immune system, the invasion of pathogens triggers a series of actions from multiple cell types to protect th...
We experimented with a suite of machine learning algorithm on the resulting representation of source code to identify how CWE pattern in both C/C++ and Java can be detected in this abstract representation, with good results in detection with low false positives rates, which makes this approach a...