Large intersubject variability is a well-described feature of fMRI studies, making inter-group inference, of critical importance for biological interpretation, difficult. Therefor...
Martin J. McKeown, Junning Li, Xuemei Huang, Z. Ja...
Content-based audio classification techniques have focused on classifying events that are both semantically and perceptually distinct (such as speech, music, environmental sounds...
This paper proposes a way of modelling the time-varying spectral energy distribution of musical instrument sounds. The model consists of an excitation signal, a body response fil...
In this paper, we propose a novel adaptive beamforming algorithm with enhanced noise suppression capability. The proposed algorithm incorporates the sound-source presence probabil...
Finding geometric and photometric relation among images is crucial in many computer vision tasks such as panoramic imaging, high dynamic range imaging, stereo imaging, and change ...
Many content-based image retrieval applications suffer from small sample set and high dimensionality problems. Relevance feedback is often used to alleviate those problems. In thi...
We propose a speech separation method for a meeting situation, where each speaker sometimes speaks and the number of speakers changes every moment. Many source separation methods ...
Frequency domain optical coherence tomography (FDOCT) is a new technique that is well-suited for fast imaging of biological specimens, as well as non-biological objects. The measu...
S. Chandra Sekhar, Himanshu Nazkani, Thierry Blu, ...
A novel technique for detecting single and multi-note ornaments is presented. The system detects audio segments by utilising an onset detector based on comb filters (ODCF), which ...
This paper introduces a composite learning approach for image retrieval with relevance feedback. The proposed system combines the radial basis function (RBF) based lowlevel learni...