3 accepted papers
Transformer models have demonstrated their promising potential and achieved excellent performance on a series of computer vision tasks. However, the huge computational cost of vision transformers hinders their deployment and application to edge devices. Recent works have proposed to find and remove t…
Channel pruning is a promising technique of model compression and acceleration because it reduces the space and time complexity of convolutional neural networks (CNNs) while maintaining their performance. In existing methods, channel pruning is performed by iterative optimization or training with sp…
Although lots of arrhythmia classification models based on deep neural networks have been proposed, most of them can only be directly applied to inputs of a fixed length, which means the raw ECG records need to be padded or truncated before being put into the model. However, this process brings two…