The technology we use, and even rely on, in our everyday lives –computers, radios, video, cell phones – is enabled by signal processing. Learn More »
1. IEEE Signal Processing Magazine
2. Signal Processing Digital Library*
3. Inside Signal Processing Newsletter
4. SPS Resource Center
5. Career advancement & recognition
6. Discounts on conferences and publications
7. Professional networking
8. Communities for students, young professionals, and women
9. Volunteer opportunities
10. Coming soon! PDH/CEU credits
Click here to learn more.
News and Resources for Members of the IEEE Signal Processing Society
Researchers from University of California, Berkeley have developed an AI that turns a horse video into a zebra video.
The following is from the abstract of the authors' paper, titled "Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks".
Image-to-image translation is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image using a training set of aligned image pairs. However, for many tasks, paired training data will not be available. We present an approach for learning to translate an image from a source domain X to a target domain Y in the absence of paired examples. Our goal is to learn a mapping G: X → Y such that the distribution of images from G(X) is indistinguishable from the distribution Y using an adversarial loss. Because this mapping is highly under-constrained, we couple it with an inverse mapping F: Y → X and introduce a cycle consistency loss to push F(G(X)) ≈ X (and vice versa). Qualitative results are presented on several tasks where paired training data does not exist, including collection style transfer, object transfiguration, season transfer, photo enhancement, etc. Quantitative comparisons against several prior methods demonstrate the superiority of our approach.
For more details, please visit https://junyanz.github.io/CycleGAN/.
AI Learns to Synthesize Pictures of Animals
Courtesy of Two Minute Papers
|Nominate an IEEE Fellow today!||1 March 2023|
|Call for Officer Nominations: President-Elect, Vice President-Conferences, and Vice President-Publications||3 March 2023|
|Call for Nominations: IEEE T-MM 2023 Multimedia Prize Paper Award||31 March 2023|
|Call for Nominations: Board of Governors Members-at-Large and Regional Directors-at-Large||7 April 2023|
|Call for Nominations: IEEE Medals & Recognitions||15 June 2023|
© Copyright 2023 IEEE – All rights reserved. Use of this website signifies your agreement to the IEEE Terms and Conditions.
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.