Autism spectrum disorder (ASD) is a highly disabling mental disease that...
Explainability poses a major challenge to artificial intelligence (AI)
t...
Deep learning models offer superior performance compared to other machin...
Integrating the brain structural and functional connectivity features is...
Multi-modal integration and classification based on graph learning is am...
We review the use of combinatorial optimisation algorithms to identify
a...
Accurate diagnosis of autism spectrum disorder (ASD) based on neuroimagi...
The development of noninvasive brain imaging such as resting-state funct...
Generative Adversarial Networks (GAN) have promoted a variety of applica...
The novel corona virus (Covid-19) has introduced significant challenges ...
Federated Learning (FL) is an emerging decentralized learning framework
...
From crying to babbling and then to speech, infant's vocal tract goes th...
Traditional goal-oriented dialogue systems rely on various components su...
We propose an approach of graph convolutional networks for robust infant...
Deep learning has gained great success in various classification tasks.
...
Deep neural networks have achieved great success both in computer vision...
Graphs can be used to effectively represent complex data structures. Lea...
Machine learning techniques are immensely deployed in both industry and
...
Convolutional Neural Networks (CNN) have gained great success in many
ar...
Improving performance of deep learning models and reducing their trainin...
Building open domain conversational systems that allow users to have eng...
Conversational agents are exploding in popularity. However, much work re...
This paper aims to develop a new architecture that can make full use of ...
This paper aims to develop a new and robust approach to feature
represen...
The rapid growth of emerging information technologies and application
pa...