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 ...

Altuna Akalin and his team at the Max Delbrück Center have developed a new tool to more precisely guide cancer treatment. Described in a paper published in “Nature Communications,” the tool, called ...

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

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: ...

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

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

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

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

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

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

In this study, an integrated artificial intelligence (AI)-atomic force microscopy (AFM) platform is introduced that enables ...