Fig. 1: Deep learning-driven adaptive optics for single-molecule localization microscopy. Upon the acquisition of camera frames, detected single-molecule emission patterns from stochastic lateral and axial positions are isolated and sent to a trained DNN. The network outputs a vector of mirror deforma...
J Cheminform|DeepSA:深度学习驱动的化合物可合成性预测 2023年11月2日,上海科技大学白芳老师团队在J Cheminform上发表文章DeepSA:a deep-learning driven predictor of compound synthesis accessibility。 作者提出了一个基于深度学习的计算模型DeepSA,用于预测化合物的可合成性(synthesis accessibility,SA),为分子筛选提...
Deep Learning-Driven Data Curation and Model Interpretation for Smart Manufacturing. Chin. J. Mech. Eng. 34, 71 (2021). https://doi.org/10.1186/s10033-021-00587-y Download citation Received10 December 2020 Revised25 May 2021 Accepted21 June 2021 Published16 July 2021 DOIhttps://doi.org/...
用神经网络,对行人和周围环境进行建模(空间上下文)和行人的方向建模(时间上下文)。 估计出行人与周围环境的交互和方向后,设计具体的损失函数,使path在可能出现的地方和可能的方向时loss最小。 缺点: 只对行人与静态环境的交互性进行建模,没有考虑行人本身的动态信息。 方法: 1、构建spatial Matching Network。 输...
This result demonstrated the power of the deep learning-based methods for the prediction of biosynthetic processes, while the higher accuracy of BioChem + USPTO_NPL than BioChem + USPTO_NPL (ses2seq) demonstrated the value of the attention mechanism by transformer. Hereafter, we would use the ...
Feng, T., Yang, B. & Lu, G. Deep learning-driven molecular dynamics simulations of molten carbonates: 1. Local structure and transport properties of molten Li2CO3-Na2CO3system.Ionics28, 1231–1248 (2022). https://doi.org/10.1007/s11581-021-04429-8...
We adopted deep learning to serve the purpose of SIM (DL-SIM) and SRRF (DL-SRRF) reconstruction, particularly with a reduced number of frames. We could also restore high resolution information from raw data with extreme low photon budgets. ...
The context model is learning to enable the detection to adapt to changes in the environment, and a is the learning rate. Suppose a frame of image does not match any Gaussian distribution during the detection process. In that case, the pattern with the most negligible weight is replaced. ...
(https://hauliang.github.io/read-list/2021/model-driven-deep-learning/) Paper List Learning fast Approximations of sparse coding (2010, ICML) Deep ADMM-Net for compressive sensing MRI (2016, NIPS) ADMM-CSNet: A deep learning Approach for image compressive sensing (2018, TPAMI) ...
and how such models can be applied to problems in speech recognition, natural language processing, and other areas. And we'llspeculate about the future of neural networks and deep learning, ranging from ideas like intention-driven user interfaces, to the role of deep learning in artificial intell...