Deep learning-based high-resolution remote sensing for farmland extraction is a crucial method for obtaining large-scale farmland information. However, variations in crop types, growth conditions, and ...

Semantic segmentation of high-resolution remote sensing images is vital in downstream applications such as land-cover mapping, urban planning, and disaster assessment. Existing Transformer-based ...

The High Court has directed all parties in a case challenging the alleged transfer of the Public Seal of Kenya to comply with earlier orders on the filing of responses and submissions.

If that is the case, then how come the network produces better accuracy by training with higher resolution images esp for smaller objects? And also, when i train with higher resolution images, is it ...

Thiol-reactive compounds, byproducts of wastewater chlorination, are under scrutiny for their high potential toxicity in water reuse applications. To date, a limited number of compounds have been ...

DLSS 4's upgraded Transformer-based AI Super Resolution has exited Beta, which means we'll start seeing it arrive in a lot more games.

These breakthroughs enable, for the first time, high spatiotemporal resolution and synchronous observation of multiple VOC components, with final imaging results available within minutes.