A research team has developed a novel weakly supervised deep learning method that reconstructs spectral data from inexpensive ...

Medical image segmentation is one of the most important tasks in modern healthcare. Every pixel in a scan tells a story, whether it marks a healthy cell, a cancerous growth, or a vital organ boundary.

SKIN CANCER is one of the most common malignancies, originating in the epidermis and strongly linked to excessive ultraviolet exposure from sunlight or tanning beds. In 2023 the United States recorded ...

As accurate segmentation is a prerequisite for obtaining real-time information about individual cattle, and since the algorithm of Mask R-CNN relies on the algorithm of simultaneous localization and ...

Few-shot segmentation aims to segment specific objects in a query image based on a few densely annotated images and has been extensively studied in recent years. In remote sensing, image segmentation ...

The Mask R-CNN+BiFPN model was proposed to enhance the feature fusion and improve the detection effect of early gastric cancer lesions. Compared with Mask R-CNN, the improved Mask R-CNN model has ...

Recently, the combination of remote sensing image processing and deep learning methods is an increasingly popular trend. In this paper, we combine the existing instance segmentation model Mask R-CNN ...

Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities.