Future events such as the weather or satellite trajectories are computed in tiny time steps, so the computation must be both efficient and as accurate as possible at each step lest errors pile up. A ...
BiLSTM, an ICD-11 automatic coding model using MC-BERT and label attention. Experiments on clinical records show 83.86% ...
An artificial intelligence (AI) deep learning tool that estimates the malignancy risk of lung nodules achieved high cancer detection rates while significantly reducing false-positive results. Results ...
Predicting tropical cyclones (TCs) accurately is crucial for disaster mitigation and public safety. Although the forecasting accuracy of TC tracks has improved substantially in recent decades, ...
Hosted on MSN
Deep learning tool sets benchmark for accurate rice panicle counting across growth stages
Subscribe to our newsletter for the latest sci-tech news updates. Rice panicle counting has historically relied on detection-, density-, or location-based methods. However, detection models struggle ...
Researchers in China conceived a new PV forecasting approach that integrates causal convolution, recurrent structures, attention mechanisms, and the Kolmogorov–Arnold Network (KAN). Experimental ...
The human brain is one of the most complex structures in nature, but the brain's origins stretch back hundreds of millions of years. A new study using AI deep-learning models has revealed more about ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results