Many tasks in medicine still involve substantial manual work. In many cases there is strong potential for intelligent automation by Artificial Intelligence (AI), leading possibly to a reduction in costs and man-hours, while increasing the quality of clinical service.

Separating the household aggregated energy consumption signal into its additive sub-components (the power signal from individual appliances), is called energy (power) disaggregation or non-intrusive load monitoring (NILM).

The Signal Processing Society (SPS) has 12 Technical Committees that support a broad selection of signal processing-related activities defined by the scope of the Society.

Three new Members-at-Large will take their seats on the IEEE Signal Processing Society Board of Governors beginning 1 January 2023 and will serve until 31 December 2025. Seven candidates competed for the three Member-at-Large positions. 

As an authentication method, biometrics offer unparalleled convenience and security. With very little for users to remember and do, there is also very little that they can do incorrectly, thus limiting the attack surface of an authentication system. Unfortunately, biometrics also present a challenging privacy/security tradeoff: biometric data...

Dr. Li is a Singaporean scientist, and a Chinese Teochew native. He is now a Presidential Chair Professor at the School of Data Science, The Chinese University of Hong Kong, Shenzhen, China. He did his Ph.D in digital signal processing of speech in 1990, and spent the past three decades to refine the technology. 

As the most widely-used spatial filtering approach for multi-channel signal separation, beamforming extracts the target signal arriving from a specific direction. We present an emerging approach based on multi-channel complex spectral mapping, which trains a deep neural network (DNN) to directly estimate the real and imaginary spectrograms of the target signal from those of the multi-channel noisy mixture. 

The IEEE Signal Processing Society (SPS) is happy to announce that Prof. Yonggang Wen will be the new Editor-in-Chief (EIC) of the IEEE Transactions on Multimedia (T-MM). His three-year term will be from January 2023 to December 2025.

Crowdsourcing has emerged as a powerful paradigm for tackling various machine learning, data mining, and data science tasks, by enlisting inexpensive crowds of human workers, or annotators, to accomplish learning and inference tasks.

Intelligent reflecting surface (IRS) has recently emerged as a promising paradigm for future wireless communications. Owing to its remarkable capability in reshaping the propagation environment, IRS has a great potential to boost spectral efficiency, mitigate interference, and enhance physical security.