September 2026

Variance stabilization with the generalized Anscombe transform (GAT) enables frozen Gaussian denoisers to process Poisson–Gaussian (PG) RAW noise, but its reliability depends on fitted shot/read-noise

  Maximum-likelihood expectation-maximization (MLEM) is a widely used statistical reconstruction method in computed tomography (CT), but under ill-posed acquisition it progressively amplifies high-fre

Most deep learning–based sound source localization methods rely on specific microphone array geometries, which require retraining for different configurations and lead to high cost. IPDnet is our prev

This paper investigates the optimal sensor configuration problem for bearings-only target localization. A unified analytical model for localization accuracy is established, applicable to both 2D and 3

This letter proposes LocMark, a local feature modulation-based conditional watermarking method, to address the limitation that existing watermarking methods for deepfake proactive forensics are vulner

Pillow-based ballistocardiography (BCG) enables unobtrusive cardiac monitoring, but J-peak detection is commonly learned as dense sequence labeling although the desired output is a sparse event set. T

Lipschitz regularization controls how strongly a denoising autoencoder propagates an input perturbation to its output, and has been used for photoplethysmography (PPG) denoising. We revisit the gradie

Existing subnetwork-based distributed speech enhancement (DSE) algorithms merely consider single target source scenarios and do not exploit inter-subnetwork information exchange in multi-source cases,

To address the challenge of comprehensively characterizing bearing fault features using a single sensor in complex industrial environments, a bearing fault diagnosis method integrating adaptive-poolin

Multi-scale graph neural networks have shown strong performance in multivariate time-series forecasting by integrating representations at different temporal resolutions. However, existing fusion mecha