Deep learning in electron microscopy

JM Ede - Machine Learning: Science and Technology, 2021 - iopscience.iop.org
Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …

Mix and match: A novel fpga-centric deep neural network quantization framework

SE Chang, Y Li, M Sun, R Shi, HKH So… - … Symposium on High …, 2021 - ieeexplore.ieee.org
Deep Neural Networks (DNNs) have achieved extraordinary performance in various
application domains. To support diverse DNN models, efficient implementations of DNN …

Binary complex neural network acceleration on fpga

H Peng, S Zhou, S Weitze, J Li, S Islam… - 2021 IEEE 32nd …, 2021 - ieeexplore.ieee.org
Being able to learn from complex data with phase information is imperative for many signal
processing applications. Today's real-valued deep neural networks (DNNs) have shown …

MSP: an FPGA-specific mixed-scheme, multi-precision deep neural network quantization framework

SE Chang, Y Li, M Sun, W Jiang, R Shi, X Lin… - arXiv preprint arXiv …, 2020 - arxiv.org
With the tremendous success of deep learning, there exists imminent need to deploy deep
learning models onto edge devices. To tackle the limited computing and storage resources …

Accelerating Large Scale Generative AI: A Comprehensive Study

Y Li - 2024 - search.proquest.com
We have witnessed the great success of deep learning in various domains, such as the
emerging large language models (LLMs) and Artificial General Intelligence (AGI), diffusion …

[PDF][PDF] Deep Learning in Electron Microscopy

M Learning - Advances in Electron Microscopy with Deep Learning, 2021 - arxiv.org
Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …