Marian Popescu

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 The following work outlines an approach for automatic detection and recognition of periodic pulse train signals using a multi-stage process based on spectrogram edge detection, energy projection and classification. The method has been implemented to automatically detect and recognize pulse train songs of minke whales. While the long term goal of this work(More)
 In this paper, we develop a novel method based on machine-learning and image processing to identify North Atlantic right whale (NARW) up-calls in the presence of high levels of ambient and interfering noise. We apply a continuous region algorithm on the spectrogram to extract the regions of interest, and then use grid masking techniques to generate a(More)
 In this paper, we propose a method to improve sound classification performance by combining signal features, derived from the time-frequency spectrogram, with human perception. The method presented herein exploits an artificial neural network (ANN) and learns the signal features based on the human perception knowledge. The proposed method is applied to a(More)
This paper presents a new software model designed for distributed sonic signal detection runtime using machine learning algorithms called DeLMA. A new algorithm-Acoustic Data-mining Accelerator (ADA)-is also presented. ADA is a robust yet scalable solution for efficiently processing big sound archives using distributing computing technologies. Together,(More)
Recent progress in patterned microelectrode manufacturing technology and microfluidics has opened the way to a large variety of cellular and molecular biosensor-based applications. In this extremely diverse and rapidly expanding landscape, silicon-based technologies occupy a special position, given their statute of mature, consolidated, and highly(More)
In September and October 2011, a seismic survey took place in Baffin Bay, Western Greenland, in close proximity to a marine protected area (MPA). As part of the mitigation effort, five bottom-mounted marine acoustic recording units (MARUs) collected data that were used for the purpose of measuring temporal and spectral features from each impulsive event,(More)
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