3 accepted papers
"Class imbalance poses a significant challenge in semi-supervised medical image segmentation (SSLMIS). Existing techniques face problems such as poor performance on tail classes, instability, and slow convergence speed. We propose a novel Gradient-Aware (GA) method, structured on a clear paradigm: i…
Recent advances in medical image segmentation models combine convolution with the attention mechanism which provides an effective approach to formulate long-term dependencies. However, many works either replaced the convolutional layers with attention layers or embedded attention layers into convolu…
Speech emotion recognition (SER) aims to automatically recognize emotional category for a given speech utterance. The performance of a SER system heavily relies on the effectiveness of global representation expressed at utterance level. To effectively extract such a global feature, the mainstream of…