2 citations · 5 across the 8 of their papers we have counts for
8 papers
X-MLP: A Patch Embedding-Free MLP Architecture for Vision
Xinyue Wang, Zhicheng Cai, Chenglei Peng
Convolutional neural networks (CNNs) and vision transformers (ViT) have obtained great achievements in computer vision. Recently, the research of multi-layer perceptron (MLP) archi…
Learn to Enhance the Negative Information in Convolutional Neural Network
Zhicheng Cai, Chenglei Peng, Qiu Shen
This paper proposes a learnable nonlinear activation mechanism specifically for convolutional neural network (CNN) termed as LENI, which learns to enhance the negative information…
FalconNet: Factorization for the Light-weight ConvNets
Zhicheng Cai, Qiu Shen
Designing light-weight CNN models with little parameters and Flops is a prominent research concern. However, three significant issues persist in the current light-weight CNNs: i) t…
Evolution: A Unified Formula for Feature Operators from a High-level Perspective
Zhicheng Cai
Traditionally, different types of feature operators (e.g., convolution, self-attention and involution) utilize different approaches to extract and aggregate the features. Resemblan…
SA-GD: Improved Gradient Descent Learning Strategy with Simulated Annealing
Zhicheng Cai
Gradient descent algorithm is the most utilized method when optimizing machine learning issues. However, there exists many local minimums and saddle points in the loss function, es…
Interflow: Aggregating Multi-layer Feature Mappings with Attention Mechanism
Zhicheng Cai
Traditionally, CNN models possess hierarchical structures and utilize the feature mapping of the last layer to obtain the prediction output. However, it can be difficulty to settle…
Jitter: Random Jittering Loss Function
Zhicheng Cai, Chenglei Peng, Sidan Du
Regularization plays a vital role in machine learning optimization. One novel regularization method called flooding makes the training loss fluctuate around the flooding level. It…
Reborn Mechanism: Rethinking the Negative Phase Information Flow in Convolutional Neural Network
Zhicheng Cai, Kaizhu Huang, Chenglei Peng
This paper proposes a novel nonlinear activation mechanism typically for convolutional neural network (CNN), named as reborn mechanism. In sharp contrast to ReLU which cuts off the…