Modern multi-layer perceptron (MLP) models have shown competitive results in learning
visual representations without self-attention. However, existing MLP models are not good at …

Recently, transformer and multi-layer perceptron (MLP) architectures have achieved
impressive results on various vision tasks. However, how to effectively combine those …

The rank of neural networks measures information flowing across layers. It is an instance of
a key structural condition that applies across broad domains of machine learning. In …

Traffic accidents caused by distracted drivers account for a large proportion of traffic
accidents each year, and monitoring the driving state of drivers to avoid traffic accidents …

Personalized image aesthetics assessment (IAA) aims to estimate aesthetic experiences
subject to the preferences of individual users, contrary to generic IAA that estimates …

MLP-Mixer is a vision architecture that solely relies on multilayer perceptrons (MLPs), which
despite their simple architecture, they achieve a slightly inferior accuracy to the state-of-the …

Backpropagation (BP) algorithm is one of the most basic learning algorithms in deep
learning. Although BP has been widely used, it still suffers from the problem of easily falling …

With the success of Transformers in the computer vision field, the automated design of vision
Transformers has attracted significant attention. Recently, MetaFormer found that simple …

Abstract Existing Binary Neural Networks (BNNs) mainly operate on local convolutions with
binarization function. However, such simple bit operations lack the ability of modeling …

With the rapid development of deep learning, training Big Models (BMs) for multiple
downstream tasks becomes a popular paradigm. Researchers have achieved various …