Knowing a little more about how biological vision works can help students to recognize what’s behind the arc of computer ...

Yann LeCun, born on July 8 ... His work, particularly in the development of convolutional neural networks (CNNs), has been instrumental in advancing deep learning technologies that underpin ...

Turing's 1950 paper didn't just pose the profound question, "Can machines think?". It ignited a quest to build AI technology ...

Current AI-methods exhibit notable limitations, such as limited application in downscaling Global Climate Models (GCMs), and accurately representing extremes. To address these challenges, we implement ...

The dual-channel graph convolutional neural networks based on hybrid features jointly model the different features of networks, so that the features can learn each other and improve the performance of ...

Aiming at ameliorating the effectiveness of unsupervised cross-domain fault diagnosis of rolling bearings, a deep transferable convolution neural network (DTCNN) based upon cooperative domain ...

@inproceedings{su2020dgc, title={Dynamic Group Convolution for Accelerating Convolutional Neural Networks}, author={Su, Zhuo and Fang, Linpu and Kang, Wenxiong and Hu, Dewen and Pietik{\"a}inen, Matti ...

In the research on lateral interaction, most studies have taken the synapse as the basic unit, including the lateral interaction in the convolutional neural network (Cheng et al., 2020) or that in the ...