The beauty of wavelets is that they are intuitively graspable while being grounded in deep mathematical foundations. As Gabor wavelets are representative of visual perceptive fields, wavelets have been used to model biological principles of vision. Wavelets have in turn proved useful to extract information from brain activity, by focusing on repeating patterns that emerge from noise. While machines are particularly apt at recognizing repetitive patterns, humans are experts at detecting departures from regularity. Neural markers related to departures from regularity are correlates of human attention, independently of sensory modality. Machines can be trained to measure this trace of attention in neural signals, which can provide novel ways to mediate communication between humans.
De Eero Simoncelli
De Naoki Saito
De Maarten de Hoop
De Martin Vetterli
De Maureen Clerc
De Irène Waldspurger
De Jérôme Kalifa
De Gitta Kutyniok
De Michael Unser
De Edouard Oyallon
De Remi Gribonval
De Ronnie Pavlov
De Viviane Pons
De Wolfgang Arendt
De David Hewett
