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Section: Publications & Resources
Publication: IEEE Signal Processing Letters
Although deep convolutional neural networks (DCNN) show significant improvement for single depth map (SD) super-resolution (SR) over the traditional counterparts, most SDSR DCNNs do not reuse the hierarchical features for depth map SR resulting in blurred high-resolution (HR) depth maps. They always stack convolutional layers to make network deeper and wider.
Section: Publications & Resources
Publication: IEEE Signal Processing Letters
A significantly low cost and tractable progressive learning approach is proposed and discussed for efficient spatiotemporal monitoring of a completely unknown, two dimensional correlated signal distribution in localized wireless sensor field. The spatial distribution is compressed into a number of its contour lines and only those sensors that their sensor observations are in a margin of the contour levels are reporting to the information fusion center (FC).
Section: Publications & Resources
Publication: IEEE Transactions on Multimedia
Using deep convolutional neural networks (CNN) to predict the depth from a single image has received considerable attention in recent years due to its impressive performance. However, existing methods process each single image independently without leveraging the multiview information of video sequences in practical scenarios.
Section: Publications & Resources
Publication: IEEE Transactions on Multimedia
The scalable video coding extensions of the High Efficient Video Coding (HEVC) standard (SHVC) have adopted a new quadtree-structured coding unit (CU). The SHVC test model (SHM) needs to test seven intermode sizes and one intramode size at depth levels of “0,” “1,” “2,” and four intermode sizes and two intramode sizes at a depth level of “3” for interframe CUs.
Section: Publications & Resources
Publication: IEEE Transactions on Multimedia
Generating images via a generative adversarial network (GAN) has attracted much attention recently. However, most of the existing GAN-based methods can only produce low-resolution images of limited quality. Directly generating high-resolution images using GANs is nontrivial, and often produces problematic images with incomplete objects.
Section: Publications & Resources
Distributed machine learning algorithms enable learning of models from datasets that are distributed over a network without gathering the data at a centralized location. While efficient distributed algorithms have been developed under the assumption of faultless networks, failures that can render these algorithms nonfunctional occur frequently in the real world.
Section: Publications & Resources
Heat-related injuries have long been a serious focus for the military, and the number reported cases has been climbing sharply in recent years. In 2018, statistics indicated that there were 578 diagnoses cases of heat stroke and more than 2,000 reported incidents of diagnosed heat exhaustion among active service members.
Section: Publications & Resources
Rabab Ward's career includes many firsts, particularly for women in engineering and signal processing, paving the way in three continents and spanning over four decades. This did not come as easy as we discovered. After many years of perseverance, Ward became the first woman with a Ph.D. to be appointed as professor of electrical engineering in Canada in 1981.
Section: Publications & Resources
In accordance with the Bylaws of the IEEE Signal Processing Society, I am writing to solicit nominations for the Awards Board and the Nominations and Appointments (N&A) Committee. This year, the Society will be filling THREE positions on the N&A Committee for the term 2020-21 and TWO positions on the Awards Board for the term 2020-2022.
Section: Publications & Resources
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