Popular Pages
Today's:
- Information for Authors
- IEEE Transactions on Information Forensics and Security
- Governance Documents
- Inside Signal Processing Newsletter
- Membership
- Information for Authors-SPL
- IEEE Transactions on Multimedia
- Community & Involvement
- (ASRU 2025) 2025 IEEE Automatic Speech Recognition and Understanding Workshop
- (SampTA 2025) 2025 International Conference on Sampling Theory and Applications
- Conferences & Events
- IEEE Signal Processing Letters
- Video & Image Processing Cup
- IEEE Transactions on Signal Processing
- IEEE JSTSP Special Issue on High-Dimensional Imaging: Emerging Challenges and Advances in Reconstruction and Restoration
All time:
- Information for Authors
- Submit a Manuscript
- IEEE Transactions on Image Processing
- IEEE Transactions on Information Forensics and Security
- IEEE Transactions on Multimedia
- IEEE Transactions on Audio, Speech and Language Processing
- IEEE Signal Processing Letters
- IEEE Transactions on Signal Processing
- Conferences & Events
- IEEE Journal of Selected Topics in Signal Processing
- Information for Authors-SPL
- Conference Call for Papers
- Signal Processing 101
- IEEE Signal Processing Magazine
- Guidelines
Last viewed:
- (ASRU 2025) 2025 IEEE Automatic Speech Recognition and Understanding Workshop
- Improved Networking Capabilities with IEEE memberNet
- (MMSP 2025) 2025 IEEE 26th International Workshop on Multimedia Signal Processing
- Guidelines for Associate Editors
- Login
- Dataset Resources
- Contests in Signal Processing and Machine Learning
- Award Recipients
- Information for Authors
- Submit a Manuscript
- Acoustic Echo Cancellation Challenge: Datasets and Testing Framework - ICASSP 2021
- Publications Board
- Apple announces new machine learning API to make mobile AI faster
- IEEE Signal Processing Letters
- Information for Authors-SPL
SPS Feed
Top Reasons to Join SPS Today!
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.
The Latest News, Articles, and Events in Signal Processing
Kinship recognition is a prominent research aiming to find if kinship relation exists between two different individuals. In general, child closely resembles his/her parents more than others based on facial similarities. These similarities are due to genetically inherited facial features that a child shares with his/her parents. Most existing researches in kinship recognition focus on full facial images to find these kinship similarities.
Non-line-of-sight (NLOS) imaging and tracking is an emerging technology that allows the shape or position of objects around corners or behind diffusers to be recovered from transient, time-of-flight measurements. However, existing NLOS approaches require the imaging system to scan a large area on a visible surface, where the indirect light paths of hidden objects are sampled.
Geometry calibration is an inherent challenge in distributed acoustic sensor networks. To mitigate this problem, a passive geometry calibration approach based on distributed damped Newton optimization is proposed. Specifically, a geometric cost function incorporating direction of arrivals (DoAs) and time difference of arrivals (TDoAs) is first formulated, and then its identifiability conditions are given.
In magnetic resonance imaging (MRI), several images can be obtained using different imaging settings (e.g. T1, T2, DWI, and Flair). These images have similar anatomical structures but are with different contrasts, which provide a wealth of information for diagnosis.
As a fundamental algorithm for collaborative processing over multi-agent systems, distributed consensus algorithm has been studied for optimizing its convergence rate. Due to the close analogy between the diffusion problem and the consensus algorithm, the previous trend in the literature is to transform the diffusion system from the spatially continuous domain into the spatially discrete one.
Graph neural networks have emerged as a popular and powerful tool for learning hierarchical representation of graph data. In complement to graph convolution operators, graph pooling is crucial for extracting hierarchical representation of data in graph neural networks. However, most recent graph pooling methods still fail to efficiently exploit the geometry of graph data. In this paper, we propose a novel graph pooling strategy that leverages node affinity to improve the hierarchical representation learning of graph data.
In order to perform network analysis tasks, representations that capture the most relevant information in the graph structure are needed. However, existing methods learn representations that cannot be interpreted in a straightforward way and that are relatively unstable to perturbations of the graph structure. We address these two limitations by proposing node2coords, a representation learning algorithm for graphs, which learns simultaneously a low-dimensional space and coordinates for the nodes in that space.
Open faculty position at KU Leuven, Belgium: junior professor in reinforcement learning
Manuscript Due: November 30, 2021
Publication Date: August 2022
CFP Document
IEEE Signal Processing Society Past President Ali H. Sayed, in his capacity as Chair of the Society’s Nominations and Appointments Committee, invites nominations for the IEEE Signal Processing Society Officer positions of President-Elect for the term 1 January 2022-31 December 2023 and Vice President-Technical Directions for the term 1 January 2022-31 December 2024.
Face recognition has become a key technology in our society, frequently used in multiple applications, while creating an impact in terms of privacy. As face recognition solutions based on artificial intelligence (AI) are becoming popular, it is critical to fully understand and explain how these technologies work in order to make them more effective and accepted by society.
The IEEE Signal Processing Society (SPS) invites nominations for the position of Editor-in-Chief for the following journals: IEEE Journal of Selected Topics in Signal Processing, IEEE/ACM Transactions on Audio, Speech, and Language Processing, IEEE Transactions on Computational Imaging, IEEE Transactions on Information Forensics and Security, and IEEE Transactions on Signal and Information Processing over Networks for a 3-year term starting 1 January 2022.
Each year, the IEEE Board of Directors confers the grade of Fellow on up to one-tenth of one percent of the voting members. To qualify for consideration, an individual must have been a Member, normally for five years or more, and a Senior Member at the time for nomination to Fellow.
Did you know the Society offers funding under the Member Driven Initiatives program for events that encourage involvement by SPS membership, including local chapters, universities, industry members as well as individual members?
This IEEE Signal Processing Society (SPS) Chapter Certification program is now accepting applications for review in 2021. This is open to all Chapters who are not currently certified, or whose certification will end on 31 December 2021.
Signal sampling and reconstruction is a fundamental engineering task at the heart of signal processing. The celebrated Shannon-Nyquist theorem guarantees perfect signal reconstruction from uniform samples, obtained at a rate twice the maximum frequency present in the signal.
Pages
SPS Social Media
- IEEE SPS Facebook Page https://www.facebook.com/ieeeSPS
- IEEE SPS X Page https://x.com/IEEEsps
- IEEE SPS Instagram Page https://www.instagram.com/ieeesps/?hl=en
- IEEE SPS LinkedIn Page https://www.linkedin.com/company/ieeesps/
- IEEE SPS YouTube Channel https://www.youtube.com/ieeeSPS
IEEE SPS Educational Resources
IEEE SPS Resource Center
IEEE SPS YouTube Channel
