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The Latest News, Articles, and Events in Signal Processing
The IEEE Signal Processing Society (SPS) announces the 2023 Class of Distinguished Lecturers and Distinguished Industry Speakers for the term of 1 January 2023 to 31 December 2024. The IEEE SPS Distinguished Lecturer (DL) Program provides a means for Chapters to have access to well-known educators and authors in the fields of signal processing to lecture at Chapter meetings.
Date: 10-13 December 2023
Location: Los Sueños, Costa Rica
Date: 17-20 September 2023
Location: Rome, Italy
Date: 22-25 October 2023
Location: New Paltz, NY, USA
Submission Deadline: 3 February 2023
Call for Proposal Document
Are you looking for innovative ways to energize and collaborate with your local signal processing community? Consider hosting a Seasonal School or Member Driven Initiative!
March 21-24, 2023
Location: Snowbird, UT, USA
Date: 15-17 February 2023
Registeration Deadline: N/A
Location: Pakistan
Date: 5-10 December 2022
Registeration Deadline: 25 November 2022
Location: Andhra Pradesh, India
Manuscript Due: 1 March 2023
Publication Date: July 2024
CFP Document
Audio pattern recognition is an important research topic in the machine learning area, and includes several tasks such as audio tagging, acoustic scene classification, music classification, speech emotion classification and sound event detection. In this blog, we introduce pretrained audio neural networks (PANNs) trained on the large-scale AudioSet dataset. These PANNs are transferred to other audio related tasks. We investigate the performance and computational complexity of PANNs modeled by a variety of convolutional neural networks. We propose an architecture called Wavegram-Logmel-CNN using both log-mel spectrogram and waveform as input feature.
Recent years, face recognition has made a remarkable breakthrough due to the emergence of deep learning. However, compared with frontal face recognition, many deep face recognition models still suffer serious performance degradation when handling profile faces. To address this issue, we propose a novel Frontal-Centers Guided Loss (FCGFace) to obtain highly discriminative features for face recognition. Most existing discriminative feature learning approaches project features from the same class into a separated latent subspace.
Date: 13 December 2022
Time: 10:00 AM ET (New York Time)
Title: Deep Learning for All-in-Focus Imaging
Registration | Full webinar details
Date: 6 December 2022
Time: 3:00 PM (Central European Time (CET))
Title: Artificial Intelligence for Applications in Neurology
Registration | Full webinar details
Brain data are inherently large scale, multidimensional, and noisy. Indeed, advances in imaging and sensor technology allow recordings of ever-increasing spatio-temporal resolution. Multidimensional, as time series data are recorded at multiple locations (electrodes, voxels), from multiple subjects, under various conditions.
Date: 14 December 2022
Time: 3:00 PM (Paris Time)
Title: Subgraph-Based Networks for Expressive, Efficient, and Domain-Independent Graph Learning
Date: 21 December 2022
Time: 8:00 AM (PST) | 5:00 PM (CET)
Title: Active Inference
Full webinar details
In the cognitive neurosciences and machine learning, we have formal ways of understanding and characterising perception and decision-making; however, the approaches appear very different: current formulations of perceptual synthesis call on theories like predictive coding and Bayesian brain hypothesis.
While message-passing neural networks (MPNNs) are the most popular architectures for graph learning, their expressive power is inherently limited. In order to gain increased expressive power while retaining efficiency, several recent works apply MPNNs to subgraphs of the original graph.
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- THIS WEEK: Join NASA’s Dr. Jacqueline Le Moigne as she shares her journey through academia, the private sector, and pivotal roles at NASA, emphasizing her work in signal processing, computer vision, and related technologies. Register now! https://x.com/IEEEsps/status/1785057479606288505
- Join NASA’s Dr. Jacqueline Le Moigne for this interactive webinar as she shares her journey through the realms of signal processing, computer vision, and related technologies, including her pivotal roles at NASA. https://x.com/IEEEsps/status/1782468413551423536
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