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This letter proposes a new approach to nonnegative Tucker decomposition, which assumes recursive updates of latent factors with any nonnegative matrix factorization algorithm. The proposed strategy is extended to the nonnegatively constrained hierarchical Tucker decomposition model.
This paper presents an intelligent system named Magic-wall, which enables visualization of the effect of room decoration automatically. Concretely, given an image of the indoor scene and a preferred color, the Magic-wall can automatically locate the wall regions in the image and smoothly replace the existing wall with the required one.
In this paper, we present a multichannel cross-modal fusion algorithm to combine two complementary modalities in electron tomography: X-ray spectroscopy and scanning transmission electron microscopy (STEM). The former reveals compositions with high elemental specificity but low signal-to-noise ratio (SNR), while the latter characterizes the structure with high SNR but little chemical information.
In this paper, we present a spatial-temporal attention-aware learning (STAL) method for video-based person re-identification. Most existing person re-identification methods aggregate image features identically to represent persons, which are extracted from the same receptive field across video frames.
Lecture Date: September 11, 2019
Chapter: Italy
Chapter Chair: Mauro Barni
Topic: Distributed Learning and Signal Processing Algorithms
Online Applications Only: http://emea3.mrted.ly/28n6x
The University of Luxembourg is a multilingual, international research university.
Several funded research opportunities are available in the Biomedical Image Computing Group at the University of New South Wales, Sydney, Australia. The group is based jointly in the School of Computer Science and Engineering and the Graduate School of Biomedical Engineering within the Faculty of Engineering.