[HTML][HTML] Beyond explaining: Opportunities and challenges of XAI-based model improvement
Abstract Explainable Artificial Intelligence (XAI) is an emerging research field bringing
transparency to highly complex and opaque machine learning (ML) models. Despite the …
transparency to highly complex and opaque machine learning (ML) models. Despite the …
Progress in prediction of remaining useful life of hydrogen fuel cells based on deep learning
W He, T Liu, W Ming, Z Li, J Du, X Li, X Guo… - … and Sustainable Energy …, 2024 - Elsevier
Hydrogen fuel cells are promising power sources that directly transform the chemical energy
produced by the chemical reaction of hydrogen and oxygen into electrical energy. However …
produced by the chemical reaction of hydrogen and oxygen into electrical energy. However …
Global attention mechanism: Retain information to enhance channel-spatial interactions
A variety of attention mechanisms have been studied to improve the performance of various
computer vision tasks. However, the prior methods overlooked the significance of retaining …
computer vision tasks. However, the prior methods overlooked the significance of retaining …
Fcanet: Frequency channel attention networks
Attention mechanism, especially channel attention, has gained great success in the
computer vision field. Many works focus on how to design efficient channel attention …
computer vision field. Many works focus on how to design efficient channel attention …
Rotate to attend: Convolutional triplet attention module
D Misra, T Nalamada… - Proceedings of the …, 2021 - openaccess.thecvf.com
Benefiting from the capability of building inter-dependencies among channels or spatial
locations, attention mechanisms have been extensively studied and broadly used in a …
locations, attention mechanisms have been extensively studied and broadly used in a …
EPSANet: An efficient pyramid squeeze attention block on convolutional neural network
Recently, it has been demonstrated that the performance of a deep convolutional neural
network can be effectively improved by embedding an attention module into it. In this work, a …
network can be effectively improved by embedding an attention module into it. In this work, a …
Dual-sampling attention network for diagnosis of COVID-19 from community acquired pneumonia
The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has
infected more than 1,436,000 people in more than 200 countries and territories as of April 9 …
infected more than 1,436,000 people in more than 200 countries and territories as of April 9 …
Feature refinement and filter network for person re-identification
In the task of person re-identification, the attention mechanism and fine-grained information
have been proved to be effective. However, it has been observed that models often focus on …
have been proved to be effective. However, it has been observed that models often focus on …
Attention, please! A survey of neural attention models in deep learning
A de Santana Correia, EL Colombini - Artificial Intelligence Review, 2022 - Springer
In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …
limited ability to process competing sources, attention mechanisms select, modulate, and …
Facial action unit detection with transformers
Abstract The Facial Action Coding System is a taxonomy for fine-grained facial expression
analysis. This paper proposes a method for detecting Facial Action Units (FAU), which …
analysis. This paper proposes a method for detecting Facial Action Units (FAU), which …