This paper proposes a lightweight and efficient railway region extraction model LRseg,
which provides technical support for detecting foreign objects on the railway. LRseg consists …

The analysis of breast cancer using Ultrasounds, Magnetic resonance imaging (MRI), and
Mammogram images plays a crucial role in the early detection of breast tumors in women …

We present a novel semi-supervised framework for breast ultrasound (BUS) image
segmentation which is a very challenging task owing to (1) large scale and shape variations …

Deep learning shows excellent performance in medical image segmentation. However, a
pooling operation in its encoding stage leads to feature loss and the ability of multi-scale …

The precise identification and localization of fish entities within visual data is essential in
diverse domains, such as marine biology and fisheries management, within computer vision …

Blood smear analysis is often used to diagnose diseases like malaria, Anemia, Leukemia,
etc. Morphological changes, such as size, shapes, and color, are receiving much attention in …

While computer vision has proven valuable for medical image segmentation, its application
faces challenges such as limited dataset sizes and the complexity of effectively leveraging …

Bringing autonomy on board edge devices is inevitable to accelerate the process of space
exploration. Although there are various tasks that can be executed autonomously by such …

Artificial intelligence-based segmentation models can assist the early-stage detection of
lung COVID-19 infections or lesions from medical images with higher efficiency versus …

Accurate diagnosis and treatment planning for medical conditions rely heavily on the results
of medical image segmentation. Medical images are available in many modalities like CT …