An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

The integration of deep learning in biodiesel research accelerates feedstock evaluation and optimizes production, making it ...

In the previous chapter, we learned various strategies to guide AI models 'down the mountain' (optimization algorithms), such ...

Nearly 50 new cancer therapies are approved every year. This is good news. "But for patients and their treating physicians, ...

Deep learning models, particularly Convolutional Neural Networks (CNN), are the core technologies for current Chinese handwriting recognition. The workflow can be summarized in the following steps: ...

Machine learning algorithms have been used to predict cancer progression, identify early signs of Parkinson’s disease, and ...

The intersection of artificial intelligence and healthcare continues to unlock unprecedented opportunities for improving patient outcomes and operational efficiency. As healthcare organizations ...

Transformer models adapted from natural language processing, such as BERT, identify semantic flaws in code, including ...

In cellular automata, simple rules create elaborate structures. Now researchers can start with the structures and ...

Deep learning has advanced rapidly, driving breakthroughs in image recognition, natural language processing, and autonomous ...

In 540p-to-1080p comparisons, NSS improves stability and detail retention. It performs well in scenes with fast motion, ...

Researchers developed and validated a label-free, non-invasive method combining AFM with deep learning for accurate profiling ...