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The Latest News, Articles, and Events in Signal Processing
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.
The IEEE Signal Processing Society Boston Chapter has been selected as the recipient of the 2022 Chapter of the Year Award!
Postdoc in Signal Processing and Machine Learning for cyber security of sensor equipped connected vehicle networks
Outstanding candidate will pursue important new research results and document them in the top journals and conferences.
IEEE Fellow is the highest grade of membership of the IEEE. It honors members with an outstanding record of technical achievements, contributing importantly to the advancement or application of engineering, science and technology, and bringing significant value to society.
Post-Doc position in multisensory signal processing and machine learning at Aalto University, Finland
IEEE SPS has built a streamlined mechanism for employers to add a job announcement by simply filling in a simple job opportunity submission Web form related to a particular TC field. To submit job announcements for a particular Technical Committee, the submission form can be found by visiting the page below and selecting a particular TC.
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.
Greetings to everyone as we prepare to celebrate the 75th anniversary of SPS during 2023! Membership of SPS, or any group, is based on the relationships, built between members. The IEEE Signal Processing Society has observed that sustained relationships lead to sustained membership growth. In its efforts to build a large and strong base of membership, SPS has spent the past few years focusing its attention on Student Members.
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