Through a novel combination of machine learning and atomic force microscopy, researchers in China have unveiled the molecular surface structure of "premelted" ice, resolving a long-standing mystery ...
The special Collection “Machine learning for automated experimentation in STEM” explores all aspects of the integration of machine learning (ML) into STEM to transform experimental workflows. This ...
New model extracts stiffness and fluidity from AFM data in minutes, enabling fast, accurate mechanical characterization of living cells at single-cell resolution. (Nanowerk Spotlight) Cells are not ...
The image pair captured in the banner shows the reduction in noise and increase in image quality between standard FDK imaging (left) and Zeiss DeepRecon Pro (right). Metal syntactic foam sample ...
It is the computational processing of images that reveals the finest details of a sample placed under all kinds of different light microscopes. Even though this processing has come a long way, there ...
System schematic for automatic detection of sister chromatid exchanges. Machine learning techniques have been used to develop a set of algorithms that can identify and count SCEs in microscopy images.
It is the computational processing of images that reveals the finest details of a sample placed under all kinds of different light microscopes. Even though this processing has come a long way, there ...
Thought LeadersDr. Nikhil Gupta & Dr. Kaushik YanamandraProf. of Mechanical and Aerospace Engineering & Applications Development EngineerNew York University & ZEISS Microscopy In this interview, ...
Multiphoton microscopy combined with deep learning can rapidly and accurately identify pancreatic neuroendocrine tumors, offering a potential tool for real-time surgical guidance Pancreatic ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results