The rapid development of spatial transcriptomics allows the measurement of RNA
abundance at a high spatial resolution, making it possible to simultaneously profile gene …

Multimodal magnetic resonance imaging (MRI) provides complementary information for sub-
region analysis of brain tumors. Plenty of methods have been proposed for automatic brain …

Deep neural networks have achieved remarkable performance for artificial intelligence
tasks. The success behind intelligent systems often relies on large-scale models with high …

In this paper, we propose a novel self-distillation method for fake speech detection (FSD),
which can significantly improve the performance of FSD without increasing the model …

Deep neural networks (DNNs) have recently achieved impressive success across a wide
range of real-world vision and language processing tasks, spanning from image …

Deep learning has achieved notable success across academia, medicine, and industry. Its
ability to identify complex patterns in large-scale data and to manage millions of parameters …

Existing unsupervised person re-identification (Re-ID) methods have achieved remarkable
performance by adopting an alternate clustering-training manner. However, they still suffer …

As a main branch of weakly supervised learning paradigm, partial label learning (PLL)
copes with the situation where each sample corresponds to ambiguous candidate labels …

The global outbreak of the Coronavirus 2019 (COVID-19) has overloaded worldwide
healthcare systems. Computer-aided diagnosis for COVID-19 fast detection and patient …

In the task of multi-label classification, it is a key challenge to determine the correlation
between labels. One solution to this is the Target Embedding Autoencoder (TEA), but most …