The sparsity of Deep Neural Networks is well investigated to maximize th...
Unsupervised person re-identification has achieved great success through...
The sensitivity of deep neural networks to compressed images hinders the...
Few-shot class-incremental learning (FSCIL) aims at learning to classify...
Due to the binary spike signals making converting the traditional high-p...
Person Re-identification (Re-ID) has attracted great attention due to it...
With the help of special neuromorphic hardware, spiking neural networks
...
Recently, the generalization behavior of Convolutional Neural Networks (...
Open set recognition (OSR), aiming to simultaneously classify the seen
c...
One of the biggest challenges in multi-agent reinforcement learning is
c...
Open set recognition is an emerging research area that aims to simultane...
Person re-identification (Re-ID) across multiple datasets is a challengi...
Many reality tasks such as robot coordination can be naturally modelled ...