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Representative: Ashish Pandharipande (12/31/27)
Steering Committee Chair: Vince Calhoun (12/31/26)Steering Committee Representatives: Selin Aviyente (12/31/26)Dimitri Van De Ville (12/31/26)
Section: Publications & Resources
How do home assistants understand your spoken words? Signal processing, of course!
In our newest video, Signal Processing in Home Assistants, we explore how signal processing engineers use signal processing and machine learning to make home assistant technology possible.
Section: Publications & Resources
The IEEE Signal Processing Magazine page has a new look on the IEEE Signal Processing Society (SPS) website, and you can access it anywhere! The new page showcases the leading-edge content in a new design format.
Section: Publications & Resources
The MMSP 2018 team is inviting you to submit regular and special session papers to MMSP2018, the annual workshop organized by the Multimedia Signal Processing Technical Committee (MMSP TC) of the IEEE Signal Processing Society.
Section: Publications & Resources
Nikos Sidiropoulos
SPS Vice President-Membership
Deadline: 4 June 2018
Section: Publications & Resources
The IEEE Signal Processing Society (SPS) invites nominations for the positions of: Chapters Committee Chair, Education Committee Chair, and Seasonal Schools Subcommittee Chair. The term for all three positions is three years (1 January 2019-31 December 2021).
Section: Publications & Resources
The IEEE Signal Processing Society invites nominations for the new SPS Distinguished Industry Speaker (DIS) Program and the Distinguished Lecturer (DL) Program. Please note that the Distinguished Industry Speaker positions will supplement the regular Distinguished Lecturer Program.
Section: Publications & Resources
We encourage applications from outstanding candidates with strong academic backgrounds in Mathematics, Physics, Computer Science, Engineering and related fields. At Inria we seek to increase the number of women in areas where they are underrepresented and therefore explicitly encourage women to apply.
Section: Publications & Resources
Researchers from UC Berkeley have developed a deep learning model that can automatically transfer your font style. The model is named multi-content generative adversarial network (MC-GAN).
