Fatima M. Felisberti

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Face recognition algorithms perform very unreliably when the pose of the probe face is different from the gallery face: typical feature vectors vary more with pose than with identity. We propose a generative model that creates a one-to-many mapping from an idealized "identity" space to the observed data space. In identity space, the representation for each(More)
Crowding, the difficult identification of peripherally viewed targets amidst similar distractors, has been explained as a compulsory pooling of target and distractor features. The tilt illusion, in which the difference between two adjacent gratings' orientations is exaggerated, has also been explained by pooling (of Mexican-hat-shaped population responses).(More)
Human observers can extract a given motion direction from sets of random dots moving simultaneously in two or more directions in the same region of the visual field, a phenomenon referred to as motion transparency. As a necessary condition for separating transparent motion directions, low level encoding of local motion signals must generate frequency(More)
Postdoctoral training is a typical step in the course of an academic career, but very little is known about postdoctoral researchers (PDRs) working in the UK. This study used an online survey to explore, for the first time, relevant environmental factors which may be linked to the research output of PDRs in terms of the number of peer-reviewed articles per(More)
The effect of the spatial location of faces in the visual field during brief, free-viewing encoding in subsequent face recognition is not known. This study addressed this question by tagging three groups of faces with cheating, cooperating or neutral behaviours and presenting them for encoding in two visual hemifields (upper vs. lower or left vs. right).(More)
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