Breast cancer (BC) is one of the topmost causes of mortality in women all over the world.
Early detection and classification of the tumor allow proper treatment of patients and …

Long sequence time-series forecasting (LSTF) is a significant and challenging task. Many
real-world applications require long-term forecasting of time series. In recent years …

Accurate semantic segmentation is crucial for monitoring the quality of metal surfaces in
industrial production. To solve the issues of the scarce quantities and uneven distributions of …

Ultrasound is a commonly used imaging modality for breast cancer diagnosis and prognosis
but suffers from false positives, false negatives and interobserver variability. Deep learning …

Training samples for deep learning networks are typically obtained through various field
experiments, which require significant manpower, resource and time consumption …

This review article discusses the roles of federated learning (FL) and transfer learning (TL) in
cancer detection based on image analysis. These two strategies powered by machine …

U-Net 及其变体模型在乳腺医学图像分割领域展现了卓越的性能, U-Net 采用全卷积网络(FCN)
结构进行语义分割, U-Net 对称结构的高度灵活性和适应性可以通过调整网络深度 …

Since the emergence of the Transformer, many variations of the original architecture have
been created. Revisions and taxonomies have appeared that group these models from …

Breast cancer stands as a prevalent form of neoplastic disease afflicting women worldwide,
with timely detection playing a pivotal role in ensuring favorable treatment outcomes. In this …

Cancers are getting pretty common these days and in that the second most common cancer
in the world after lung cancer is breast cancer. The primary screening techniques for early …