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

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

A research team at UCLA, led by Professor Aydogan Ozcan, has introduced BlurryScope, a compact, cost-effective scanning ...

The thesis not only showcases technical advancements but also underscores the importance of interpretability and scalability in agricultural AI solutions. Farmers and stakeholders are more likely to ...

In this research, we set out to investigate whether elementary biological learning systems achieve performance levels that can compete with state-of-the-art deep RL algorithms.

This work provides a paradigm for applying advanced deep learning–assisted Raman spectroscopy in substance identification, enhancing understanding of Raman spectral information at the sub ...

Researchers have developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal ...

Researchers developed a deep learning-based multimodal prognostic model that shows strong potential to improve disease-free ...

Onc.AI’s poster presentation showcases its FDA-breakthrough designated deep learning radiomics model, Serial CTRS, which evaluates changes across routine CT scans over time to predict overall ...