Abstract Transformers are Deep Neural Networks (DNN) that utilize a self-attention
mechanism to capture contextual relationships within sequential data. Unlike traditional …

Skin cancer is a major public health problem that could benefit from computer-aided
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …

The segmentation algorithm for buildings and waters is extremely important for the efficient
planning and utilization of land resources. The temporal and space range of remote sensing …

The transformer is primarily used in the field of natural language processing. Recently, it has
been adopted and shows promise in the computer vision (CV) field. Medical image analysis …

The current advancement towards retinal disease detection mainly focused on distinct
feature extraction using either a convolutional neural network (CNN) or a transformer-based …

Ischemic stroke is a cerebrovascular disease with a high morbidity and mortality rate, which
poses a serious challenge to human health and life. Meanwhile, the management of …

Background and objective: The diagnosis of BI-RADS category 4 breast lesion is difficult
because its probability of malignancy ranges from 2% to 95%. For BI-RADS category 4 …

Cervical cytology image classification is of great significance to the cervical cancer
diagnosis and prognosis. Recently, convolutional neural network (CNN) and visual …

Satellite‐based optical video sensors are poised as the next frontier in remote sensing.
Satellite video offers the unique advantage of capturing the transient dynamics of floods with …

Hyperspectral images (HSIs) encompass data across numerous spectral bands, making
them valuable in various practical fields such as remote sensing, agriculture, and marine …