Diabetic retinopathy is a serious complication needing prompt diagnosis and medication to
avert vision loss. Lesions caused by the condition are difficult to track because they are …

The objective of this review is to conduct a critical analysis of the current literature pertaining
to segmentation techniques and provide a methodical summary of their impact on forestry …

Wildfire is a hazardous natural phenomenon that leads to significant human fatalities,
catastrophic environmental damages, and economic losses. Over the past few years, the …

The production of highly accurate land cover maps is one of the primary challenges in
remote sensing, which depends on the spatial resolution of the input images. Sometimes …

Urban road extraction is important for the applications of urban planning and transportation.
High-resolution image (HRI) has been one of the most popular data sources for extracting …

Semantic segmentation of high-resolution remote sensing images plays an important role in
many practical applications, including precision agriculture and natural disaster assessment …

The common channel attention mechanism maps feature statistics to feature weights.
However, the effectiveness of this mechanism may not be assured in remotely sensing …

Skin lesion segmentation is an indispensable step in the diagnostic process of skin
diseases. Using deep learning networks for skin lesion segmentation can enhance the work …

Deep learning has proven to be highly successful at semantic segmentation of remote
sensing images (RSIs); however, it remains challenging due to the significant intraclass …

With developments in deep learning, semantic segmentation of remote sensing images has
made great progress. Currently, mainstream methods are based on convolutional neural …