Tag: U-Net

Deep learning models trained on 35,060 synthetic image pairs automatically remove salt-and-pepper noise, ring artifacts, and beam-hardening distortions from micro-CT ...

Researchers in India have built a unified deep learning framework that classifies brain tumors in MRI scans with 98.52 percent ...

Researchers have combined a phase-dependent signal preprocessing step with a dual U-Net deep learning framework to reconstruct planar antenna array ...

Researchers at VIT-AP University have developed TF-Mamba-DPHNet, a compact Mamba-based AI framework that removes noise from speech while preserving fine ...

A new dual-branch U-Net called PDSA-DBUNet combines dynamic sparse attention with a polynomial mixer to achieve record abdominal CT segmentation ...

A two-stage Vision Transformer–U-Net pipeline restores reliable detection of rare voids in concrete X-ray CT images where single-stage deep learning ...

A new hybrid deep learning architecture combining a fine-tuned U-Net with a time-weighted multi-task bi-directional LSTM significantly improves real-time detection ...

Researchers have built a hybrid transformer-U-Net that segments diabetic foot ulcers with expert-level overlap and quantitatively explainable visualisations.

Researchers have developed CHS-Net, a hybrid deep learning architecture that sets a new benchmark for segmenting cracks, erosion, and delamination ...

Researchers have developed a dual-stream convolutional neural network that fuses RGB imagery with vectorized Error Level Analysis and CBAM attention ...