In addition, we develop the dual deep learning network with weight sharing to fully extract the registration pair image features. The proposed method is tested on different period Landsat-7 and ...

Scientists in Malaysia have developed a novel deep-learning method for PV suitability mapping. Applying the new approach to the Middle East, they found that approximately 5.8% of the region has very ...

A Model-Based Unsupervised Deep Learning Method for Low-Dose CT Reconstruction Low-dose CT (LDCT) is of great significance due to the concern about the potential radiation risk. With the fast ...

Deep learning not only can produce useful results where other methods fail, but also can build more accurate models than other methods, and can reduce the time needed to build a useful model.

Scientists have developed a geometric deep learning method that can create a coherent picture of neuronal population activity during cognitive and motor tasks across experimental subjects and ...

Researchers demonstrated how a deep learning framework they call 'Brain-NET' can accurately predict a person's level of expertise in terms of their surgical motor skills, based solely on ...

Achieving collaboration in deep learning by using institutional incremental learning to address data sharing and security issues. Applicable to object detection problems for various domains.

The NeoPulse Framework promises to ease the burden of developing Deep Learning models by introducing a number of interesting concepts.