Abstract Seamlessly blending features from multiple images is extremely challenging because of complex relationships in lighting, geometry, and partial occlusion which cause coupling between different ...

Semantic segmentation is critical in medical image processing, with traditional specialist models facing adaptation challenges to new tasks or distribution shifts. While both generalist pre-trained ...

Meta Platforms Inc. today is expanding its suite of open-source Segment Anything computer vision models with the release of SAM 3 and SAM 3D, introducing enhanced object recognition and ...

KALAMAZOO, Mich. (WOOD) — Masks will no longer be used by investigators working with the Kalamazoo Valley Enforcement Team, the police chief says. Kalamazoo Department of Public Safety Chief David ...

Segmentation of Biomedical Images is based on U-Net. This U-Net implementation using Keras and TensorFlow has varying depth that can be specified by model input.

Abstract: Ultrasound imaging is widely used in clinical practice due to its advantages of no radiation and real-time capability. However, its image quality is often degraded by speckle noise, low ...

Introduction: Breast cancer is a severe illness predominantly affecting women, and in most cases, it leads to loss of life if left undetected. Early detection can significantly reduce the mortality ...

The MHSAttResDU-Net incorporates RCC for complexity control and improved generalization under varying lighting. The SSRP unit in encoder-decoder blocks reduces feature map dimensions, capturing key ...