MLCommons Releases MLPerf Training v6.0 Results

Today, MLCommons ® announced new results for the MLPerf ® Training v6.0 benchmark suite. The two new benchmarks added in this ...
Nature

Autonomous fabrication of tailored defect structures in 2D materials using machine learning-enabled scanning transmission electron microscopy

It is significantly more expensive to generate enough labeled training data, either through simulations or by manual labeling of experimental data, to train the computer vision models specifically for ...
Frontiers

Reproducible supervised learning-assisted classification of spontaneous synaptic waveforms with Eventer

Detection and analysis of spontaneous synaptic events is an extremely common task in many neuroscience research labs. Various algorithms and tools have been developed over the years to improve the ...
C&EN

Human–Machine Interaction via Dual Modes of Voice and Gesture Enabled by Triboelectric Nanogenerator and Machine Learning

College of Mathematics and Physics, Shanghai Key Laboratory of Materials Protection and Advanced Materials in Electric Power, Shanghai University of Electric Power, Shanghai 200090, China Beijing Key ...
Frontiers

A Machine Learning Approach for Detecting Vicarious Trial and Error Behaviors

Vicarious trial and error behaviors (VTEs) indicate periods of indecision during decision-making, and have been proposed as a behavioral marker of deliberation. In ...
Nature

Single Molecule Fluorescence Microscopy and Machine Learning for Rhesus D Antigen Classification

In transfusion medicine, the identification of the Rhesus D type is important to prevent anti-D immunisation in Rhesus D negative recipients. In particular, the detection of the very low expressed DEL ...