New approach improves the prediction accuracy of agronomically relevant traits
The classical approach of genomic prediction (GP) in crops trains machine learning
The Polybot project is receiving €220,000 to develop an intelligent harvesting robot that promotes sustainable agriculture.
With the support, we can now train our learning algorithms on the most difficult
The Polybot project is receiving €220,000 to develop an intelligent harvesting robot that promotes sustainable agriculture.
With the support, we can now train our learning algorithms on the most difficult
The making of a quantum movie
Only pulses from such a complete wave train are inherently so stable that they can
The making of a quantum movie
Only pulses from such a complete wave train are inherently so stable that they can
New approach improves the prediction accuracy of agronomically relevant traits
The classical approach of genomic prediction (GP) in crops trains machine learning
In the online world users’ attention is a precious currency, and online environments are designed to capture and steer that attention. Yet users and legislators currently have little to say in how these environments are regulated and controlled; How can we respond to these challenges of the digital age and how might the design of the online world be improved? A team of researchers addressed these questions from the perspective of behavioral science and now propose some answers.
They suggest that “boosting tools” can be used to train new competencies and enable
Bavaria invests up to 500 million euros in the competitive development of the Martinsried Max Planck Campus into an outstanding international research hub
designed meeting centre for science and the public near the future underground train
Deep learning algorithms facilitate the analysis of mass spectrometry data.
the interpretation of mass spectrometry spectra., They used machine learning to train
A team of researchers in Tübingen show that optical flow systems based on deep neural networks – a likely component of future autonomous cars – are vulnerable to adversarial attacks. The computer vision experts are shaking up the automotive industry by warning car manufacturers around the globe that it could take a simple colour pattern to put the brakes on computer vision systems in autonomous cars.
self-driving technology that there is a new possible threat and enable them to train
