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Section: Publications & Resources

Publication: IEEE Transactions on Image Processing

Despite the rapid progress of restoration-aware compression, existing studies still face challenges in low-bitrate restoration scenarios. Real-world image acquisition is inevitably affected by degrada

Section: Publications & Resources

Publication: IEEE Transactions on Image Processing

Recently, Mamba-based super-resolution (SR) methods have demonstrated the ability to capture global receptive fields with linear complexity, addressing the quadratic computational cost of Transformer-

Section: Publications & Resources

Publication: IEEE Transactions on Image Processing

In semi-supervised object detection (SSOD), due to the limited availability of labeled data, the quality and quantity of pseudo labels generated from unlabeled images are crucial for model training. O

Section: Publications & Resources

Publication: IEEE Transactions on Image Processing

Facial emotion recognition (FER) has traditionally focused on a limited set of basic expressions, often failing to capture the complexity, subtlety, and cultural variability of real-world human emotio

Section: Publications & Resources

Publication: IEEE Signal Processing Letters

Weakly supervised semantic segmentation (WSSS) with image-level labels is largely limited by the reliability of dense seed supervision. Existing CAM- and CLIP-based methods provide complementary local

Section: Publications & Resources

Publication: IEEE Signal Processing Letters

State-of-the-art no-reference video quality assessment (NR-VQA) methods for conventional 2D videos achieve remarkable performance by leveraging quality-sensitive local spatial fragments. However, dire

Section: Publications & Resources

Publication: IEEE Signal Processing Letters

Differential beamforming enables compact arrays to synthesize frequency-invariant, highly directive beampatterns, but existing formulations for arbitrary planar geometries assume omnidirectional or, a

Section: Publications & Resources

Publication: IEEE Signal Processing Letters

We propose an Adaptive Kernel Bayes Filter (AKBF) that integrates the kernel Bayes rule with explicit dynamical models. Particles are evolved in data space while their kernel mean embeddings are propa

Section: Publications & Resources

Publication: IEEE Signal Processing Letters

Due to the large approximation errors, current omega-k algorithms for multireceiver synthetic aperture sonar (MSAS) fail to achieve high-quality results. To address this issue, this letter presents a

Section: Publications & Resources

Publication: IEEE Signal Processing Letters

This letter studies a Fourier-probe obstruction test for structured residue-class derivative sampling of analytic functions. At each of two sampling points, only derivatives whose orders lie in prescr