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Section: Publications & Resources

Publication: IEEE Signal Processing Letters

Scene-Text Visual Question Answering (STVQA) is a comprehensive task that requires reading and understanding the text in images to answer the question. Existing methods of exploring the vision-language relationships between questions, images, and scene text have achieved impressive results. However, these studies heavily rely on auxiliary modules, such as external OCR systems and object detection networks, making the question-answering process cumbersome and highly dependent.

Section: Publications & Resources

Publication: IEEE Signal Processing Letters

Single-satellite geolocation achieves effective localization of ground electromagnetic interference (EMI) signals with a low cost compared to the multi-satellite counterparts. In such systems, the Doppler and Doppler rate are commonly exploited to extract the information of the ground EMI sources and the constrained Unscented Kalman filter (cUKF) is found effective to provide instantaneous EMI locations over time. 

Section: Publications & Resources

Publication: IEEE Signal Processing Letters

We consider the problem of recovering off-the-grid spikes from linear measurements in the context of Single Molecule Localization Microscopy (SMLM). State of the art model-based methods such as Over-Parametrized Continuous Orthogonal Matching Pursuit (OP-COMP) with Projected Gradient Descent (PGD) have been shown to successfully recover those signals. 

Section: Publications & Resources

The IEEE Signal Processing Society (SPS) will hold a Special Election to fill the vacant President-Elect position, which will open on 6 February 2025 and close on 26 March 2025.

Section: Publications & Resources

The IEEE SPS congratulates the following SPS members who will receive the Society’s prestigious awards during ICASSP 2025 in India.

Section: Publications & Resources

Publication: IEEE Transactions on Computational Imaging

While snapshot hyperspectral cameras are cheaper and faster than imagers based on pushbroom or whiskbroom spatial scanning, the output imagery from a snapshot camera typically has different spectral bands mapped to different spatial locations in a mosaic pattern, requiring a demosaicing process to be applied to generate the desired hyperspectral image with full spatial and spectral resolution.

Section: Publications & Resources

Publication: IEEE Transactions on Computational Imaging

Magnetic Resonance Imaging (MRI) is a widely used imaging technique, however it has the limitation of long scanning time. Though previous model-based and learning-based MRI reconstruction methods have shown promising performance, most of them have not fully utilized the edge prior of MR images, and there is still much room for improvement.

Section: Publications & Resources

Publication: IEEE Transactions on Computational Imaging

We introduce ICE-TIDE, a method for cryogenic electron tomography (cryo-ET) that simultaneously aligns observations and reconstructs a high-resolution volume. The alignment of tilt series in cryo-ET is a major problem limiting the resolution of reconstructions. ICE-TIDE relies on an efficient coordinate-based implicit neural representation of the volume which enables it to directly parameterize deformations and align the projections.

Section: Publications & Resources

Publication: IEEE Journal of Selected Topics in Signal Processing

Signal processing techniques have played a pivotal role in the early development of joint sensing and communication systems [1]. These efforts were driven by the need to address spectrum scarcity and to reduce hardware size and cost. Initially focused on dual-function radar-communication systems, this field has since evolved into the broader paradigm of Integrated Sensing and Communication (ISAC).

Section: Publications & Resources

Publication: IEEE Journal of Selected Topics in Signal Processing

This paper proposes a Model-Based Online Learning (MBOL) framework for waveform optimization in integrated sensing and communications (ISAC) systems. In particular, the MBOL framework is proposed to enhance the ISAC performance under dynamic environmental conditions. Unlike Model-Free Online Learning (MFOL) methods, our approach leverages a rich structural knowledge of sensing, communications, and radio environments, offering better explainability and sample efficiency.