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20232026
most citedA Survey on Mixup Augmentations and Beyond

6 citations · 13 across the 14 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.CV2024

Relax DARTS: Relaxing the Constraints of Differentiable Architecture Search for Eye Movement Recognition

Hongyu Zhu, Xin Jin, Hongchao Liao +3

Eye movement biometrics is a secure and innovative identification method. Deep learning methods have shown good performance, but their network architecture relies on manual design…

cs.CV2024

EM-DARTS: Hierarchical Differentiable Architecture Search for Eye Movement Recognition

Huafeng Qin, Hongyu Zhu, Xin Jin +3

Eye movement biometrics has received increasing attention thanks to its highly secure identification. Although deep learning (DL) models have shown success in eye movement recognit…

cs.LG2024★ 6 cited

A Survey on Mixup Augmentations and Beyond

Xin Jin, Hongyu Zhu, Siyuan Li +6

As Deep Neural Networks have achieved thrilling breakthroughs in the past decade, data augmentations have garnered increasing attention as regularization techniques when massive la…

cs.CV2024

SUMix: Mixup with Semantic and Uncertain Information

Huafeng Qin, Xin Jin, Hongyu Zhu +3

Mixup data augmentation approaches have been applied for various tasks of deep learning to improve the generalization ability of deep neural networks. Some existing approaches CutM…

cs.CV2024★ 2 cited

StarLKNet: Star Mixup with Large Kernel Networks for Palm Vein Identification

Xin Jin, Hongyu Zhu, Mounîm A. El Yacoubi +4

As a representative of a new generation of biometrics, vein identification technology offers a high level of security and convenience.Convolutional neural networks (CNNs), a promin…

cs.CV2024★ 4 cited

EmMixformer: Mix transformer for eye movement recognition

Huafeng Qin, Hongyu Zhu, Xin Jin +3

Eye movement (EM) is a new highly secure biometric behavioral modality that has received increasing attention in recent years. Although deep neural networks, such as convolutional…