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Fish Detection and Tracking is an important step in studying oceanography, especially for forecasting changes in the quality of water and the increasing or decreasing number of fish in a population. In this paper, combination of Gaussian Mixture Model and Frame-Differencing algorithm (CGMMFD) is proposed to improve tracking performance in different scenarios. Also, four other techniques, namely Mean...
For a standalone Fall Detection system based on computer vision we want to obtain a low power architecture to meet the real time processing, power consumption, energy constraints which also satisfy the high performance in recognition, and accuracy. In this paper, we present the different architecture explorations for Fall Detection system implemented on heterogeneous platform as Zynq-7000 AP SoC platform...
We investigate noise reduction (NR) for speech signals for automatic speech recognition (ASR). We compare four transform based noise reduction algorithms according to their influence on ASR performance. These include frequency domain based algorithms using the discrete Fourier transform (DFT), the fast chirp transform (FCT), and the discrete wavelet transform (DWT), as well as a lattice filter based...
We present an approach to broad phonetic classification, defined as mapping acoustic speech frames into broad (or clustered) phonetic categories. Our categories consist of silence, general voiced, general unvoiced, mixed sounds, voiced closure, and plosive release, and are sufficiently rich to allow accurate time-scaling of speech signals to improve their intelligibility in, e.g. voice-mail applications...
We propose an improved noise reduction method for robust speech recognition based on a perceptually statistical wavelet filtering algorithm. Perceptual noise thresholds are estimated from the universal thresholds for each critical wavelet subband. Fast changes of background noise are tracked adaptively by improving our statistical percentile filtering method. Smoothed wavelet shrinkage is applied...
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