Superresolution structured illumination microscopy reconstruction algorithms: a review
X Chen, S Zhong, Y Hou, R Cao, W Wang… - Light: Science & …, 2023 - nature.com
Structured illumination microscopy (SIM) has become the standard for next-generation wide-
field microscopy, offering ultrahigh imaging speed, superresolution, a large field-of-view …
field microscopy, offering ultrahigh imaging speed, superresolution, a large field-of-view …
[HTML][HTML] Resolution enhancement of digital holographic microscopy via synthetic aperture: a review
Digital holographic microscopy (DHM), which combines digital holography with optical
microscopy, is a wide field, minimally invasive quantitative phase microscopy (QPM) …
microscopy, is a wide field, minimally invasive quantitative phase microscopy (QPM) …
Real-time vehicle detection based on improved yolo v5
Y Zhang, Z Guo, J Wu, Y Tian, H Tang, X Guo - Sustainability, 2022 - mdpi.com
To reduce the false detection rate of vehicle targets caused by occlusion, an improved
method of vehicle detection in different traffic scenarios based on an improved YOLO v5 …
method of vehicle detection in different traffic scenarios based on an improved YOLO v5 …
Rationalized deep learning super-resolution microscopy for sustained live imaging of rapid subcellular processes
The goal when imaging bioprocesses with optical microscopy is to acquire the most
spatiotemporal information with the least invasiveness. Deep neural networks have …
spatiotemporal information with the least invasiveness. Deep neural networks have …
A transfer learning-based CNN and LSTM hybrid deep learning model to classify motor imagery EEG signals
Abstract In the Motor Imagery (MI)-based Brain Computer Interface (BCI), users' intention is
converted into a control signal through processing a specific pattern in brain signals …
converted into a control signal through processing a specific pattern in brain signals …
A review of critical challenges in MI-BCI: From conventional to deep learning methods
Brain-computer interfaces (BCIs) have achieved significant success in controlling external
devices through the Electroencephalogram (EEG) signal processing. BCI-based Motor …
devices through the Electroencephalogram (EEG) signal processing. BCI-based Motor …
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 …
microscopy. This review paper offers a practical perspective aimed at developers with …
A survey on deep learning in medical image reconstruction
Medical image reconstruction aims to acquire high-quality medical images for clinical usage
at minimal cost and risk to the patients. Deep learning and its applications in medical …
at minimal cost and risk to the patients. Deep learning and its applications in medical …
Deep learning‐based image reconstruction for different medical imaging modalities
Image reconstruction in magnetic resonance imaging (MRI) and computed tomography (CT)
is a mathematical process that generates images at many different angles around the …
is a mathematical process that generates images at many different angles around the …
[HTML][HTML] A bird's-eye view of deep learning in bioimage analysis
E Meijering - Computational and structural biotechnology journal, 2020 - Elsevier
Deep learning of artificial neural networks has become the de facto standard approach to
solving data analysis problems in virtually all fields of science and engineering. Also in …
solving data analysis problems in virtually all fields of science and engineering. Also in …