Abstract: A novel unsupervised algorithm, named deep-learning-based error image prior (DLEIP), is proposed for lung electrical impedance tomography (EIT). An ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

@inproceedings{10.1117/12.3067427, author = {Levi Harris and Md Jayed Hossain and Mufan Qui and Ruichen Zhang and Pingchuan Ma and Tianlong Chen and Jiaqi Gu and Seth ...

Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is the ...

Learn how to effectively read and understand deep learning code with this beginner-friendly guide. Break down complex scripts and get comfortable navigating AI projects step by step. #DeepLearning ...

For over 5 years, Arthur has been professionally covering video games, writing guides and walkthroughs. His passion for video games began at age 10 in 2010 when he first played Gothic, an immersive ...

The use of AI in software development has gained traction with the emergence of large language models (LLMs). These models are capable of performing coding-related tasks. This shift has led to the ...

Conclusions: Our findings demonstrate that compared with unimodal approaches, an integrated deep learning model incorporating both imaging and clinical data has greater diagnostic accuracy for MMP in ...