6 accepted papers
Most of the artificial lights fluctuate in response to the grid's alternating current and exhibit subtle variations in terms of both intensity and spectrum, providing the potential to estimate the Electric Network Frequency (ENF) from conventional frame-based videos. Nevertheless, the performance of…
Beamforming weights prediction via deep neural networks has been one of the main methods in multi-channel speech enhancement tasks. The spectral-spatial cues are crucial in beamforming weights estimation, however, many existing works fail to optimally predict the beamforming weights with an absence…
Compressed sensing based algorithms are utilized to obtain high-resolution time-frequency distribution (TFD) with negligible cross-terms (CTs), however, performance deteriorates when the signal is composed of closely-located or overlapped components. Moreover, there is still an impressive resolution…
Blind source separation involves the estimation of mixing matrix given only observed mixtures. Considering the computational cost in practice, this paper proposes an efficient mixing matrix estimation (MME) method using an easily configured two-sensor array. Time-frequency (TF) analysis, which has b…
Visible and near-infrared (VIS-NIR) face recognition remains a challenging task due to distinctions between spectral components of two modalities. Inspired by the CycleGAN, this paper presents a method aiming to translate between VIS and NIR face images. To achieve this, we propose a new facial feat…
For the purpose of dealing with closely-spaced and spectrally-overlapped sources, a direction-of-arrival (DOA) estimation algorithm based on time-frequency (TF) sparse representation is proposed. Firstly a short-time Fourier transform (STFT) based single-source TF points selection method is briefly…